Last updated on 2022-06-28 07:52:00 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.3.0 | 19.42 | 615.42 | 634.84 | NOTE | |
| r-devel-linux-x86_64-debian-gcc | 1.3.0 | 15.53 | 285.89 | 301.42 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.3.0 | 500.74 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 1.3.0 | 497.80 | ERROR | |||
| r-devel-windows-x86_64 | 1.3.0 | 147.00 | 611.00 | 758.00 | NOTE | |
| r-patched-linux-x86_64 | 1.3.0 | 32.64 | 388.06 | 420.70 | ERROR | |
| r-release-linux-x86_64 | 1.3.0 | 19.31 | 394.25 | 413.56 | ERROR | |
| r-release-macos-arm64 | 1.3.0 | 418.00 | NOTE | |||
| r-release-macos-x86_64 | 1.3.0 | 412.00 | NOTE | |||
| r-release-windows-x86_64 | 1.3.0 | 140.00 | 578.00 | 718.00 | OK | |
| r-oldrel-macos-arm64 | 1.3.0 | 467.00 | NOTE | |||
| r-oldrel-macos-x86_64 | 1.3.0 | 378.00 | NOTE | |||
| r-oldrel-windows-ix86+x86_64 | 1.3.0 | 38.00 | 557.00 | 595.00 | OK |
Version: 1.3.0
Check: Rd files
Result: NOTE
checkRd: (-1) lcMethodMixAK_GLMM.Rd:47: Escaped LaTeX specials: \&
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64
Version: 1.3.0
Check: examples
Result: ERROR
Running examples in ‘latrend-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: confusionMatrix
> ### Title: Compute the posterior confusion matrix
> ### Aliases: confusionMatrix
>
> ### ** Examples
>
> data(latrendData)
>
> if (rlang::is_installed("lcmm")) {
+ method <- lcMethodLcmmGMM(
+ fixed = Y ~ Time,
+ mixture = ~ Time,
+ random = ~ 1,
+ id = "Id",
+ time = "Time"
+ )
+ model <- latrend(method, latrendData)
+ confusionMatrix(model)
+ }
---------------------------------------------------------------------------
- Longitudinal clustering using: growth mixture model
---------------------------------------------------------------------------
Method arguments:
mixture: ~Time
random: ~1
classmb: ~1
time: "Time"
id: "Id"
init: "default"
nClusters: 2
idiag: FALSE
nwg: FALSE
cor: NULL
convB: 1e-04
convL: 1e-04
convG: 1e-04
pprior: NULL
maxiter: 500
na.action: 1
posfix: NULL
var.time: NULL
partialH: FALSE
nproc: 1
clustertype: NULL
fixed: Y ~ Time
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Error in (function (fixed, mixture, random, subject, classmb, ng = 1, :
Please specify initial values with argument 'B'
Calls: latrend ... suppressFun -> fit -> fit -> gmm_fit -> do.call -> <Anonymous>
Execution halted
Flavors: r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [80s/120s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(latrend)
>
> test_check('latrend')
[ FAIL 3 | WARN 1 | SKIP 9 | PASS 2174 ]
══ Skipped tests ═══════════════════════════════════════════════════════════════
• On CRAN (7)
• empty test (1)
• skipping MixTVEM tests because the TVEMMixNormal() function is not loaded (1)
══ Failed tests ════════════════════════════════════════════════════════════════
── Error (test-lcmm.R:35:3): gmm ───────────────────────────────────────────────
Error in `test.latrend("lcMethodLcmmGMM", instantiator = make.gmm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:35:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:36:4
── Error (test-lcmm.R:55:3): gmm with NA covariate ─────────────────────────────
Error in `test.latrend("lcMethodLcmmGMM", instantiator = make.gmm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:55:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:56:4
── Error (test-lcmm.R:73:3): gbtm ──────────────────────────────────────────────
Error in `test.latrend("lcMethodLcmmGBTM", instantiator = make.gbtm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:73:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:74:4
[ FAIL 3 | WARN 1 | SKIP 9 | PASS 2174 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.3.0
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
...
--- re-building ‘demo.Rmd’ using rmarkdown
---------------------------------------------------------------------------
- Longitudinal clustering using: longitudinal k-means (KML)
---------------------------------------------------------------------------
Method arguments:
time: getOption("latrend.time")
id: getOption("latrend.id")
nClusters: 2
nbRedrawing: 1
maxIt: 200
imputationMethod:"copyMean"
distanceName: "euclidean"
power: 2
distance: function() {}
centerMethod: meanNA
startingCond: "nearlyAll"
nbCriterion: 1000
scale: TRUE
response: "Y"
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.51 secs)
---------------------------------------------------------------------------
Quitting from lines 151-154 (demo.Rmd)
Error: processing vignette ‘demo.Rmd’ failed with diagnostics:
task 2 failed - "Please specify initial values with argument 'B'"
--- failed re-building ‘demo.Rmd’
--- re-building ‘implement.Rmd’ using rmarkdown
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: meanNA
nClusters: NaN
clusterNames: NULL
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: Y[1] > 1.6
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.036 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: mean
nClusters: NaN
clusterNames: NULL
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: stratfun
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.18 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: meanNA
nClusters: NaN
clusterNames: c("Low", "High")
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: Intercept[1] > 1.7
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.046 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: two-step clustering
---------------------------------------------------------------------------
Method arguments:
standardize: scale
center: meanNA
time: getOption("latrend.time")
id: getOption("latrend.id")
response: "Y"
representationStep:repStep
clusterStep: clusStep
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.19 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: two-step clustering
---------------------------------------------------------------------------
Method arguments:
nClusters: 2
formula: Y ~ Time
standardize: scale
center: meanNA
time: getOption("latrend.time")
id: getOption("latrend.id")
response: "Y"
representationStep:repStep.gen
clusterStep: clusStep.gen
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.31 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: simple group-based trajectory model
---------------------------------------------------------------------------
Method arguments:
formula: Y ~ Time
time: "Time"
id: "Traj"
nClusters: 2
nwg: FALSE
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Quitting from lines 357-359 (implement.Rmd)
Error: processing vignette ‘implement.Rmd’ failed with diagnostics:
Please specify initial values with argument 'B'
--- failed re-building ‘implement.Rmd’
--- re-building ‘simulation.Rmd’ using rmarkdown
--- finished re-building ‘simulation.Rmd’
--- re-building ‘validation.Rmd’ using rmarkdown
--- finished re-building ‘validation.Rmd’
SUMMARY: processing the following files failed:
‘demo.Rmd’ ‘implement.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.3.0
Check: dependencies in R code
Result: NOTE
Namespace in Imports field not imported from: ‘rmarkdown’
All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-release-macos-arm64, r-release-macos-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Version: 1.3.0
Check: examples
Result: ERROR
Running examples in ‘latrend-Ex.R’ failed
The error most likely occurred in:
> ### Name: confusionMatrix
> ### Title: Compute the posterior confusion matrix
> ### Aliases: confusionMatrix
>
> ### ** Examples
>
> data(latrendData)
>
> if (rlang::is_installed("lcmm")) {
+ method <- lcMethodLcmmGMM(
+ fixed = Y ~ Time,
+ mixture = ~ Time,
+ random = ~ 1,
+ id = "Id",
+ time = "Time"
+ )
+ model <- latrend(method, latrendData)
+ confusionMatrix(model)
+ }
---------------------------------------------------------------------------
- Longitudinal clustering using: growth mixture model
---------------------------------------------------------------------------
Method arguments:
mixture: ~Time
random: ~1
classmb: ~1
time: "Time"
id: "Id"
init: "default"
nClusters: 2
idiag: FALSE
nwg: FALSE
cor: NULL
convB: 1e-04
convL: 1e-04
convG: 1e-04
pprior: NULL
maxiter: 500
na.action: 1
posfix: NULL
var.time: NULL
partialH: FALSE
nproc: 1
clustertype: NULL
fixed: Y ~ Time
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Error in (function (fixed, mixture, random, subject, classmb, ng = 1, :
Please specify initial values with argument 'B'
Calls: latrend ... suppressFun -> fit -> fit -> gmm_fit -> do.call -> <Anonymous>
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [137s/158s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(latrend)
>
> test_check('latrend')
[ FAIL 3 | WARN 1 | SKIP 9 | PASS 2174 ]
══ Skipped tests ═══════════════════════════════════════════════════════════════
• On CRAN (7)
• empty test (1)
• skipping MixTVEM tests because the TVEMMixNormal() function is not loaded (1)
══ Failed tests ════════════════════════════════════════════════════════════════
── Error (test-lcmm.R:35:3): gmm ───────────────────────────────────────────────
Error in `test.latrend("lcMethodLcmmGMM", instantiator = make.gmm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:35:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:36:4
── Error (test-lcmm.R:55:3): gmm with NA covariate ─────────────────────────────
Error in `test.latrend("lcMethodLcmmGMM", instantiator = make.gmm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:55:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:56:4
── Error (test-lcmm.R:73:3): gbtm ──────────────────────────────────────────────
Error in `test.latrend("lcMethodLcmmGBTM", instantiator = make.gbtm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:73:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:74:4
[ FAIL 3 | WARN 1 | SKIP 9 | PASS 2174 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.3.0
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
--- re-building ‘demo.Rmd’ using rmarkdown
---------------------------------------------------------------------------
- Longitudinal clustering using: longitudinal k-means (KML)
---------------------------------------------------------------------------
Method arguments:
time: getOption("latrend.time")
id: getOption("latrend.id")
nClusters: 2
nbRedrawing: 1
maxIt: 200
imputationMethod:"copyMean"
distanceName: "euclidean"
power: 2
distance: function() {}
centerMethod: meanNA
startingCond: "nearlyAll"
nbCriterion: 1000
scale: TRUE
response: "Y"
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.57 secs)
---------------------------------------------------------------------------
Quitting from lines 151-154 (demo.Rmd)
Error: processing vignette 'demo.Rmd' failed with diagnostics:
task 2 failed - "Please specify initial values with argument 'B'"
--- failed re-building ‘demo.Rmd’
--- re-building ‘implement.Rmd’ using rmarkdown
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: meanNA
nClusters: NaN
clusterNames: NULL
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: Y[1] > 1.6
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.032 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: mean
nClusters: NaN
clusterNames: NULL
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: stratfun
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.38 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: meanNA
nClusters: NaN
clusterNames: c("Low", "High")
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: Intercept[1] > 1.7
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.027 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: two-step clustering
---------------------------------------------------------------------------
Method arguments:
standardize: scale
center: meanNA
time: getOption("latrend.time")
id: getOption("latrend.id")
response: "Y"
representationStep:repStep
clusterStep: clusStep
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.29 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: two-step clustering
---------------------------------------------------------------------------
Method arguments:
nClusters: 2
formula: Y ~ Time
standardize: scale
center: meanNA
time: getOption("latrend.time")
id: getOption("latrend.id")
response: "Y"
representationStep:repStep.gen
clusterStep: clusStep.gen
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.27 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: simple group-based trajectory model
---------------------------------------------------------------------------
Method arguments:
formula: Y ~ Time
time: "Time"
id: "Traj"
nClusters: 2
nwg: FALSE
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Quitting from lines 357-359 (implement.Rmd)
Error: processing vignette 'implement.Rmd' failed with diagnostics:
Please specify initial values with argument 'B'
--- failed re-building ‘implement.Rmd’
--- re-building ‘simulation.Rmd’ using rmarkdown
--- finished re-building ‘simulation.Rmd’
--- re-building ‘validation.Rmd’ using rmarkdown
--- finished re-building ‘validation.Rmd’
SUMMARY: processing the following files failed:
‘demo.Rmd’ ‘implement.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [137s/334s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(latrend)
>
> test_check('latrend')
[ FAIL 3 | WARN 1 | SKIP 9 | PASS 2174 ]
══ Skipped tests ═══════════════════════════════════════════════════════════════
• On CRAN (7)
• empty test (1)
• skipping MixTVEM tests because the TVEMMixNormal() function is not loaded (1)
══ Failed tests ════════════════════════════════════════════════════════════════
── Error (test-lcmm.R:35:3): gmm ───────────────────────────────────────────────
Error in `test.latrend("lcMethodLcmmGMM", instantiator = make.gmm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:35:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:36:4
── Error (test-lcmm.R:55:3): gmm with NA covariate ─────────────────────────────
Error in `test.latrend("lcMethodLcmmGMM", instantiator = make.gmm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:55:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:56:4
── Error (test-lcmm.R:73:3): gbtm ──────────────────────────────────────────────
Error in `test.latrend("lcMethodLcmmGBTM", instantiator = make.gbtm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:73:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:74:4
[ FAIL 3 | WARN 1 | SKIP 9 | PASS 2174 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.3.0
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
--- re-building ‘demo.Rmd’ using rmarkdown
---------------------------------------------------------------------------
- Longitudinal clustering using: longitudinal k-means (KML)
---------------------------------------------------------------------------
Method arguments:
time: getOption("latrend.time")
id: getOption("latrend.id")
nClusters: 2
nbRedrawing: 1
maxIt: 200
imputationMethod:"copyMean"
distanceName: "euclidean"
power: 2
distance: function() {}
centerMethod: meanNA
startingCond: "nearlyAll"
nbCriterion: 1000
scale: TRUE
response: "Y"
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (1.2 secs)
---------------------------------------------------------------------------
Quitting from lines 151-154 (demo.Rmd)
Error: processing vignette 'demo.Rmd' failed with diagnostics:
task 2 failed - "Please specify initial values with argument 'B'"
--- failed re-building ‘demo.Rmd’
--- re-building ‘implement.Rmd’ using rmarkdown
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: meanNA
nClusters: NaN
clusterNames: NULL
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: Y[1] > 1.6
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.12 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: mean
nClusters: NaN
clusterNames: NULL
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: stratfun
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.27 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: meanNA
nClusters: NaN
clusterNames: c("Low", "High")
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: Intercept[1] > 1.7
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.048 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: two-step clustering
---------------------------------------------------------------------------
Method arguments:
standardize: scale
center: meanNA
time: getOption("latrend.time")
id: getOption("latrend.id")
response: "Y"
representationStep:repStep
clusterStep: clusStep
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.65 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: two-step clustering
---------------------------------------------------------------------------
Method arguments:
nClusters: 2
formula: Y ~ Time
standardize: scale
center: meanNA
time: getOption("latrend.time")
id: getOption("latrend.id")
response: "Y"
representationStep:repStep.gen
clusterStep: clusStep.gen
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.99 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: simple group-based trajectory model
---------------------------------------------------------------------------
Method arguments:
formula: Y ~ Time
time: "Time"
id: "Traj"
nClusters: 2
nwg: FALSE
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Quitting from lines 357-359 (implement.Rmd)
Error: processing vignette 'implement.Rmd' failed with diagnostics:
Please specify initial values with argument 'B'
--- failed re-building ‘implement.Rmd’
--- re-building ‘simulation.Rmd’ using rmarkdown
--- finished re-building ‘simulation.Rmd’
--- re-building ‘validation.Rmd’ using rmarkdown
--- finished re-building ‘validation.Rmd’
SUMMARY: processing the following files failed:
‘demo.Rmd’ ‘implement.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [119s/132s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(latrend)
>
> test_check('latrend')
[ FAIL 3 | WARN 1 | SKIP 9 | PASS 2174 ]
══ Skipped tests ═══════════════════════════════════════════════════════════════
• On CRAN (7)
• empty test (1)
• skipping MixTVEM tests because the TVEMMixNormal() function is not loaded (1)
══ Failed tests ════════════════════════════════════════════════════════════════
── Error (test-lcmm.R:35:3): gmm ───────────────────────────────────────────────
Error in `test.latrend("lcMethodLcmmGMM", instantiator = make.gmm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:35:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:36:4
── Error (test-lcmm.R:55:3): gmm with NA covariate ─────────────────────────────
Error in `test.latrend("lcMethodLcmmGMM", instantiator = make.gmm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:55:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:56:4
── Error (test-lcmm.R:73:3): gbtm ──────────────────────────────────────────────
Error in `test.latrend("lcMethodLcmmGBTM", instantiator = make.gbtm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:73:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:74:4
[ FAIL 3 | WARN 1 | SKIP 9 | PASS 2174 ]
Error: Test failures
Execution halted
Flavor: r-patched-linux-x86_64
Version: 1.3.0
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
...
--- re-building ‘demo.Rmd’ using rmarkdown
---------------------------------------------------------------------------
- Longitudinal clustering using: longitudinal k-means (KML)
---------------------------------------------------------------------------
Method arguments:
time: getOption("latrend.time")
id: getOption("latrend.id")
nClusters: 2
nbRedrawing: 1
maxIt: 200
imputationMethod:"copyMean"
distanceName: "euclidean"
power: 2
distance: function() {}
centerMethod: meanNA
startingCond: "nearlyAll"
nbCriterion: 1000
scale: TRUE
response: "Y"
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.57 secs)
---------------------------------------------------------------------------
Quitting from lines 151-154 (demo.Rmd)
Error: processing vignette ‘demo.Rmd’ failed with diagnostics:
task 2 failed - "Please specify initial values with argument 'B'"
--- failed re-building ‘demo.Rmd’
--- re-building ‘implement.Rmd’ using rmarkdown
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: meanNA
nClusters: NaN
clusterNames: NULL
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: Y[1] > 1.6
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.045 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: mean
nClusters: NaN
clusterNames: NULL
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: stratfun
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.24 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: meanNA
nClusters: NaN
clusterNames: c("Low", "High")
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: Intercept[1] > 1.7
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.045 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: two-step clustering
---------------------------------------------------------------------------
Method arguments:
standardize: scale
center: meanNA
time: getOption("latrend.time")
id: getOption("latrend.id")
response: "Y"
representationStep:repStep
clusterStep: clusStep
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.26 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: two-step clustering
---------------------------------------------------------------------------
Method arguments:
nClusters: 2
formula: Y ~ Time
standardize: scale
center: meanNA
time: getOption("latrend.time")
id: getOption("latrend.id")
response: "Y"
representationStep:repStep.gen
clusterStep: clusStep.gen
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.32 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: simple group-based trajectory model
---------------------------------------------------------------------------
Method arguments:
formula: Y ~ Time
time: "Time"
id: "Traj"
nClusters: 2
nwg: FALSE
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Quitting from lines 357-359 (implement.Rmd)
Error: processing vignette ‘implement.Rmd’ failed with diagnostics:
Please specify initial values with argument 'B'
--- failed re-building ‘implement.Rmd’
--- re-building ‘simulation.Rmd’ using rmarkdown
--- finished re-building ‘simulation.Rmd’
--- re-building ‘validation.Rmd’ using rmarkdown
--- finished re-building ‘validation.Rmd’
SUMMARY: processing the following files failed:
‘demo.Rmd’ ‘implement.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavor: r-patched-linux-x86_64
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [118s/130s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(latrend)
>
> test_check('latrend')
[ FAIL 3 | WARN 1 | SKIP 9 | PASS 2174 ]
══ Skipped tests ═══════════════════════════════════════════════════════════════
• On CRAN (7)
• empty test (1)
• skipping MixTVEM tests because the TVEMMixNormal() function is not loaded (1)
══ Failed tests ════════════════════════════════════════════════════════════════
── Error (test-lcmm.R:35:3): gmm ───────────────────────────────────────────────
Error in `test.latrend("lcMethodLcmmGMM", instantiator = make.gmm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:35:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:36:4
── Error (test-lcmm.R:55:3): gmm with NA covariate ─────────────────────────────
Error in `test.latrend("lcMethodLcmmGMM", instantiator = make.gmm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:55:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:56:4
── Error (test-lcmm.R:73:3): gbtm ──────────────────────────────────────────────
Error in `test.latrend("lcMethodLcmmGBTM", instantiator = make.gbtm, tests = tests,
data = lcmmData)`: Unexpected error occurred while evaluating test context: "basic"
Error message:
"Please specify initial values with argument 'B'"
Stack trace:
16: sys.source(file, envir = env)
15: eval(exprs[i], envir)
14: eval(exprs[i], envir)
13: latrend(m, data = testData)
12: .fitLatrendMethod(cmethod, modelData, envir = modelEnv, mc = mc,
verbose = verbose)
11: suppressFun({
modelEnv = preFit(method = method, data = data, envir = envir,
verbose = verbose)
model = fit(method = method, data = data, envir = modelEnv,
verbose = verbose)
...
10: capture.output(suppressMessages(...))
9: withVisible(...elt(i))
8: suppressMessages(...)
7: withCallingHandlers(expr, message = function(c) if (inherits(c,
classes)) tryInvokeRestart("muffleMessage"))
6: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
5: fit(method = method, data = data, envir = modelEnv, verbose = verbose)
4: gmm_fit(method, data, envir, verbose, ...)
3: do.call(lcmm::hlme, args)
2: (function (fixed, mixture, random, subject, classmb, ng = 1,
idiag = FALSE, nwg = FALSE, cor = NULL, data, B, convB = 1e-04,
convL = 1e-04, convG = 1e-04, prior, pprior = NULL, maxiter = 500,
subset = NULL, na.action = 1, posfix = NULL, verbose = TRUE,
returndata = FALSE, var.time = NULL, partialH = FALSE, nproc = 1,
...
1: stop("Please specify initial values with argument 'B'")
Backtrace:
▆
1. ├─testthat::expect_true(...) at test-lcmm.R:73:2
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─latrend::test.latrend(...) at test-lcmm.R:74:4
[ FAIL 3 | WARN 1 | SKIP 9 | PASS 2174 ]
Error: Test failures
Execution halted
Flavor: r-release-linux-x86_64
Version: 1.3.0
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
...
--- re-building ‘demo.Rmd’ using rmarkdown
---------------------------------------------------------------------------
- Longitudinal clustering using: longitudinal k-means (KML)
---------------------------------------------------------------------------
Method arguments:
time: getOption("latrend.time")
id: getOption("latrend.id")
nClusters: 2
nbRedrawing: 1
maxIt: 200
imputationMethod:"copyMean"
distanceName: "euclidean"
power: 2
distance: function() {}
centerMethod: meanNA
startingCond: "nearlyAll"
nbCriterion: 1000
scale: TRUE
response: "Y"
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.91 secs)
---------------------------------------------------------------------------
Quitting from lines 151-154 (demo.Rmd)
Error: processing vignette ‘demo.Rmd’ failed with diagnostics:
task 2 failed - "Please specify initial values with argument 'B'"
--- failed re-building ‘demo.Rmd’
--- re-building ‘implement.Rmd’ using rmarkdown
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: meanNA
nClusters: NaN
clusterNames: NULL
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: Y[1] > 1.6
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.023 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: mean
nClusters: NaN
clusterNames: NULL
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: stratfun
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.32 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: stratify
---------------------------------------------------------------------------
Method arguments:
center: meanNA
nClusters: NaN
clusterNames: c("Low", "High")
time: getOption("latrend.time")
id: getOption("latrend.id")
name: "stratify"
response: "Y"
stratify: Intercept[1] > 1.7
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.034 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: two-step clustering
---------------------------------------------------------------------------
Method arguments:
standardize: scale
center: meanNA
time: getOption("latrend.time")
id: getOption("latrend.id")
response: "Y"
representationStep:repStep
clusterStep: clusStep
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.23 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: two-step clustering
---------------------------------------------------------------------------
Method arguments:
nClusters: 2
formula: Y ~ Time
standardize: scale
center: meanNA
time: getOption("latrend.time")
id: getOption("latrend.id")
response: "Y"
representationStep:repStep.gen
clusterStep: clusStep.gen
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Done fitting the method (0.3 secs)
---------------------------------------------------------------------------
---------------------------------------------------------------------------
- Longitudinal clustering using: simple group-based trajectory model
---------------------------------------------------------------------------
Method arguments:
formula: Y ~ Time
time: "Time"
id: "Traj"
nClusters: 2
nwg: FALSE
---------------------------------------------------------------------------
Checking and transforming the training data format.
Preparing the training data for fitting...
Fitting the method...
Quitting from lines 357-359 (implement.Rmd)
Error: processing vignette ‘implement.Rmd’ failed with diagnostics:
Please specify initial values with argument 'B'
--- failed re-building ‘implement.Rmd’
--- re-building ‘simulation.Rmd’ using rmarkdown
--- finished re-building ‘simulation.Rmd’
--- re-building ‘validation.Rmd’ using rmarkdown
--- finished re-building ‘validation.Rmd’
SUMMARY: processing the following files failed:
‘demo.Rmd’ ‘implement.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavor: r-release-linux-x86_64
Version: 1.3.0
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘mixAK’
Flavors: r-release-macos-arm64, r-release-macos-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Version: 1.3.0
Check: Rd cross-references
Result: NOTE
Package unavailable to check Rd xrefs: ‘mixAK’
Flavors: r-release-macos-arm64, r-release-macos-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64