Last updated on 2022-11-14 05:55:07 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 4.8.2 | OK | ||||
| r-devel-linux-x86_64-debian-gcc | 4.8.2 | 30.42 | 595.43 | 625.85 | OK | |
| r-devel-linux-x86_64-fedora-clang | 4.8.2 | 1006.09 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 4.8.2 | 1003.50 | OK | |||
| r-devel-windows-x86_64 | 4.8.2 | 101.00 | 780.00 | 881.00 | OK | |
| r-patched-linux-x86_64 | 4.8.2 | 37.68 | 753.59 | 791.27 | OK | |
| r-release-linux-x86_64 | 4.8.2 | 33.45 | 757.26 | 790.71 | OK | |
| r-release-macos-arm64 | 4.8.2 | 196.00 | ERROR | |||
| r-release-macos-x86_64 | 4.8.2 | 330.00 | OK | |||
| r-release-windows-x86_64 | 4.8.2 | 78.00 | 795.00 | 873.00 | OK | |
| r-oldrel-macos-arm64 | 4.8.2 | 198.00 | ERROR | |||
| r-oldrel-macos-x86_64 | 4.8.2 | 322.00 | OK | |||
| r-oldrel-windows-ix86+x86_64 | 4.8.2 | 81.00 | 840.00 | 921.00 | ERROR |
Version: 4.8.2
Check: tests
Result: ERROR
Running ‘testthat.R’ [50s/51s]
Running the tests in ‘tests/testthat.R’ failed.
Last 13 lines of output:
as.numeric(b_lincom[, 5]) not equal to 0.0005428401.
1/1 mismatches
[1] 0.016 - 0.000543 == 0.0155
── Failure ('test-parametric_bootstrap.R:170'): p-value are at least approximately uniform under null (univariate mixed-effects model) ──
max(abs(sapply(pvals, function(x) mean(pvals <= x)) - pvals)) not equal to 0.1.
1/1 mismatches
[1] 0.3 - 0.1 == 0.2
── Failure ('test-parametric_bootstrap.R:280'): simulate_betta_random does a reasonable thing ──
mean(...) not equal to 1.02.
1/1 mismatches
[1] 0.961 - 1.02 == -0.0586
[ FAIL 7 | WARN 1 | SKIP 0 | PASS 250 ]
Error: Test failures
Execution halted
Flavor: r-release-macos-arm64
Version: 4.8.2
Check: tests
Result: ERROR
Running ‘testthat.R’ [49s/50s]
Running the tests in ‘tests/testthat.R’ failed.
Last 13 lines of output:
as.numeric(b_lincom[, 5]) not equal to 0.0005428401.
1/1 mismatches
[1] 0.016 - 0.000543 == 0.0155
── Failure ('test-parametric_bootstrap.R:170'): p-value are at least approximately uniform under null (univariate mixed-effects model) ──
max(abs(sapply(pvals, function(x) mean(pvals <= x)) - pvals)) not equal to 0.1.
1/1 mismatches
[1] 0.3 - 0.1 == 0.2
── Failure ('test-parametric_bootstrap.R:280'): simulate_betta_random does a reasonable thing ──
mean(...) not equal to 1.02.
1/1 mismatches
[1] 0.961 - 1.02 == -0.0586
[ FAIL 7 | WARN 1 | SKIP 0 | PASS 250 ]
Error: Test failures
Execution halted
Flavor: r-oldrel-macos-arm64
Version: 4.8.2
Check: tests
Result: ERROR
Running 'testthat.R' [305s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> ################################################################################
> # Use testthat to test that nothing important breaks
> ################################################################################
>
> library(testthat)
> library(breakaway)
> library(phyloseq)
> library(magrittr)
Attaching package: 'magrittr'
The following objects are masked from 'package:testthat':
equals, is_less_than, not
>
> test_check("breakaway")
$estimate
[1] 2319
$error
[1] 0
$estimand
[1] "richness"
$name
[1] "Plug-in"
$interval
[1] 2319 2319
$interval_type
[1] NA
$type
[1] NA
$model
[1] "none"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] FALSE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 2319
$seest
[1] 0
$ci
[1] 2319 2319
$estimate
[1] 1000
$error
[1] 0
$estimand
[1] "richness"
$name
[1] "Plug-in"
$interval
[1] 1000 1000
$interval_type
[1] NA
$type
[1] NA
$model
[1] "none"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] FALSE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 1000
$seest
[1] 0
$ci
[1] 1000 1000
$estimate
[1] 331
$error
[1] 0
$estimand
[1] "richness"
$name
[1] "Plug-in"
$interval
[1] 331 331
$interval_type
[1] NA
$type
[1] NA
$model
[1] "none"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] FALSE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 331
$seest
[1] 0
$ci
[1] 331 331
$estimate
[1] 356
$error
[1] 0
$estimand
[1] "richness"
$name
[1] "Plug-in"
$interval
[1] 356 356
$interval_type
[1] NA
$type
[1] NA
$model
[1] "none"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] FALSE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 356
$seest
[1] 0
$ci
[1] 356 356
$estimate
[1] 349
$error
[1] 0
$estimand
[1] "richness"
$name
[1] "Plug-in"
$interval
[1] 349 349
$interval_type
[1] NA
$type
[1] NA
$model
[1] "none"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] FALSE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 349
$seest
[1] 0
$ci
[1] 349 349
$estimate
[1] 367
$error
[1] 0
$estimand
[1] "richness"
$name
[1] "Plug-in"
$interval
[1] 367 367
$interval_type
[1] NA
$type
[1] NA
$model
[1] "none"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] FALSE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 367
$seest
[1] 0
$ci
[1] 367 367
$estimate
[1] 306
$error
[1] 0
$estimand
[1] "richness"
$name
[1] "Plug-in"
$interval
[1] 306 306
$interval_type
[1] NA
$type
[1] NA
$model
[1] "none"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] FALSE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 306
$seest
[1] 0
$ci
[1] 306 306
$estimate
[1] 3181.5
$error
[1] 88.71478
$estimand
[1] "richness"
$name
[1] "chao1"
$interval
[1] 2362.714 19336.617
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 3181.5
$seest
[1] 88.71478
$ci
[1] 2362.714 19336.617
$estimate
[1] 1241.286
$error
[1] 38.05458
$estimand
[1] "richness"
$name
[1] "chao1"
$interval
[1] 1015.669 4715.556
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 1241.286
$seest
[1] 38.05458
$ci
[1] 1015.669 4715.556
$estimate
[1] 371.3333
$error
[1] 16.00014
$estimand
[1] "richness"
$name
[1] "chao1"
$interval
[1] 333.5326 973.3283
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 371.3333
$seest
[1] 16.00014
$ci
[1] 333.5326 973.3283
$estimate
[1] 367.7647
$error
[1] 6.898408
$estimand
[1] "richness"
$name
[1] "chao1"
$interval
[1] 356.9721 498.3858
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 367.7647
$seest
[1] 6.898408
$ci
[1] 356.9721 498.3858
$estimate
[1] 370.875
$error
[1] 9.677414
$estimand
[1] "richness"
$name
[1] "chao1"
$interval
[1] 350.7452 623.1820
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 370.875
$seest
[1] 9.677414
$ci
[1] 350.7452 623.1820
$estimate
[1] 381.0192
$error
[1] 7.120062
$estimand
[1] "richness"
$name
[1] "chao1"
$interval
[1] 368.2416 525.2956
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 381.0192
$seest
[1] 7.120062
$ci
[1] 368.2416 525.2956
$estimate
[1] 362.9412
$error
[1] 23.28989
$estimand
[1] "richness"
$name
[1] "chao1"
$interval
[1] 308.8149 1457.8195
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 362.9412
$seest
[1] 23.28989
$ci
[1] 308.8149 1457.8195
$estimate
[1] 3177.141
$error
[1] 88.21714
$estimand
[1] "richness"
$name
[1] "chao1_bc"
$interval
[1] 2362.649 19189.923
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 3177.141
$seest
[1] 88.21714
$ci
[1] 2362.649 19189.923
$estimate
[1] 1238.912
$error
[1] 37.69171
$estimand
[1] "richness"
$name
[1] "chao1_bc"
$interval
[1] 1015.602 4658.503
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 1238.912
$seest
[1] 37.69171
$ci
[1] 1015.602 4658.503
$estimate
[1] 368.84
$error
[1] 15.03456
$estimand
[1] "richness"
$name
[1] "chao1_bc"
$interval
[1] 333.4643 912.0415
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 368.84
$seest
[1] 15.03456
$ci
[1] 333.4643 912.0415
$estimate
[1] 366.5556
$error
[1] 6.314576
$estimand
[1] "richness"
$name
[1] "chao1_bc"
$interval
[1] 356.9099 478.4579
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 366.5556
$seest
[1] 6.314576
$ci
[1] 356.9099 478.4579
$estimate
[1] 369.5172
$error
[1] 9.168819
$estimand
[1] "richness"
$name
[1] "chao1_bc"
$interval
[1] 350.6818 599.2976
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 369.5172
$seest
[1] 9.168819
$ci
[1] 350.6818 599.2976
$estimate
[1] 380
$error
[1] 6.710938
$estimand
[1] "richness"
$name
[1] "chao1_bc"
$interval
[1] 368.1824 509.9289
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 380
$seest
[1] 6.710938
$ci
[1] 368.1824 509.9289
$estimate
[1] 358.5556
$error
[1] 21.31788
$estimand
[1] "richness"
$name
[1] "chao1_bc"
$interval
[1] 308.7484 1310.9893
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 358.5556
$seest
[1] 21.31788
$ci
[1] 308.7484 1310.9893
$estimate
[1] 4152.555
$error
[1] 291.5206
$estimand
[1] "richness"
$name
[1] "Chao-Bunge"
$interval
[1] 2358.034 88446.264
$interval_type
[1] "Approximate: log-normal"
$type
NULL
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] TRUE
$other
$other$cutoff
[1] 10
$est
[1] 4152.555
$seest
[1] 291.5206
$ci
[1] 2358.034 88446.264
$estimate
[1] 1376.942
$error
[1] 64.43054
$estimand
[1] "richness"
$name
[1] "Chao-Bunge"
$interval
[1] 1017.146 9286.904
$interval_type
[1] "Approximate: log-normal"
$type
NULL
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] TRUE
$other
$other$cutoff
[1] 10
$est
[1] 1376.942
$seest
[1] 64.43054
$ci
[1] 1017.146 9286.904
$estimate
[1] 399.445
$error
[1] 32.91482
$estimand
[1] "richness"
$name
[1] "Chao-Bunge"
$interval
[1] 333.5417 2174.1395
$interval_type
[1] "Approximate: log-normal"
$type
NULL
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] TRUE
$other
$other$cutoff
[1] 10
$est
[1] 399.445
$seest
[1] 32.91482
$ci
[1] 333.5417 2174.1395
$estimate
[1] 366.037
$error
[1] 10.48092
$estimand
[1] "richness"
$name
[1] "Chao-Bunge"
$interval
[1] 356.4582 575.8740
$interval_type
[1] "Approximate: log-normal"
$type
NULL
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] TRUE
$other
$other$cutoff
[1] 10
$est
[1] 366.037
$seest
[1] 10.48092
$ci
[1] 356.4582 575.8740
$estimate
[1] 378.7363
$error
[1] 15.09051
$estimand
[1] "richness"
$name
[1] "Chao-Bunge"
$interval
[1] 350.6699 878.5170
$interval_type
[1] "Approximate: log-normal"
$type
NULL
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] TRUE
$other
$other$cutoff
[1] 10
$est
[1] 378.7363
$seest
[1] 15.09051
$ci
[1] 350.6699 878.5170
$estimate
[1] 384.8917
$error
[1] 12.15087
$estimand
[1] "richness"
$name
[1] "Chao-Bunge"
$interval
[1] 367.9616 699.9053
$interval_type
[1] "Approximate: log-normal"
$type
NULL
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] TRUE
$other
$other$cutoff
[1] 10
$est
[1] 384.8917
$seest
[1] 12.15087
$ci
[1] 367.9616 699.9053
$estimate
[1] 337.8483
$error
[1] 14.91761
$estimand
[1] "richness"
$name
[1] "Chao-Bunge"
$interval
[1] 307.8883 843.1520
$interval_type
[1] "Approximate: log-normal"
$type
NULL
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] TRUE
$other
$other$cutoff
[1] 10
$est
[1] 337.8483
$seest
[1] 14.91761
$ci
[1] 307.8883 843.1520
$estimate
[1] 2691.593
$error
[1] 50.23337
$estimand
[1] "richness"
$name
[1] "wlrm_transformed"
$interval
[1] 2341.506 8487.342
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$para
Estimate Std. Error
(Intercept) 0.61620601 0.120062903
xs 0.08651219 0.007555332
$other$full
Call:
lm(formula = log(ys) ~ xs, weights = weights_trans)
Coefficients:
(Intercept) xs
0.61621 0.08651
$other$cutoff
[1] 63
$est
[1] 2691.593
$seest
[1] 50.23337
$ci
[1] 2341.506 8487.342
$estimate
[1] 1178.603
$error
[1] 28.17513
$estimand
[1] "richness"
$name
[1] "wlrm_transformed"
$interval
[1] 1013.925 3290.816
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$para
Estimate Std. Error
(Intercept) 0.4388526 0.12855085
xs 0.1382131 0.01625013
$other$full
Call:
lm(formula = log(ys) ~ xs, weights = weights_trans)
Coefficients:
(Intercept) xs
0.4389 0.1382
$other$cutoff
[1] 33
$est
[1] 1178.603
$seest
[1] 28.17513
$ci
[1] 1013.925 3290.816
$estimate
[1] 358.6254
$error
[1] 9.335348
$estimand
[1] "richness"
$name
[1] "wlrm_transformed"
$interval
[1] 333.6635 617.5239
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$para
Estimate Std. Error
(Intercept) 0.4654530 0.24094924
xs 0.1351371 0.02153069
$other$full
Call:
lm(formula = log(ys) ~ xs, weights = weights_trans)
Coefficients:
(Intercept) xs
0.4655 0.1351
$other$cutoff
[1] 28
$est
[1] 358.6254
$seest
[1] 9.335348
$ci
[1] 333.6635 617.5239
$estimate
[1] 363.7108
$error
[1] 3.55656
$estimand
[1] "richness"
$name
[1] "wlrm_transformed"
$interval
[1] 357.1177 409.1938
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$para
Estimate Std. Error
(Intercept) 0.9531054 0.1892241
xs 0.1134064 0.0170140
$other$full
Call:
lm(formula = log(ys) ~ xs, weights = weights_trans)
Coefficients:
(Intercept) xs
0.9531 0.1134
$other$cutoff
[1] 26
$est
[1] 363.7108
$seest
[1] 3.55656
$ci
[1] 357.1177 409.1938
$estimate
[1] 363.2128
$error
[1] 5.061292
$estimand
[1] "richness"
$name
[1] "wlrm_transformed"
$interval
[1] 350.9435 452.9358
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$para
Estimate Std. Error
(Intercept) 0.90120646 0.1750310
xs 0.09149412 0.0103463
$other$full
Call:
lm(formula = log(ys) ~ xs, weights = weights_trans)
Coefficients:
(Intercept) xs
0.90121 0.09149
$other$cutoff
[1] 41
$est
[1] 363.2128
$seest
[1] 5.061292
$ci
[1] 350.9435 452.9358
$estimate
[1] 377.768
$error
[1] 4.203355
$estimand
[1] "richness"
$name
[1] "wlrm_transformed"
$interval
[1] 368.5607 441.2943
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$para
Estimate Std. Error
(Intercept) 0.9192573 0.15849327
xs 0.1014363 0.01178144
$other$full
Call:
lm(formula = log(ys) ~ xs, weights = weights_trans)
Coefficients:
(Intercept) xs
0.9193 0.1014
$other$cutoff
[1] 34
$est
[1] 377.768
$seest
[1] 4.203355
$ci
[1] 368.5607 441.2943
$estimate
[1] 326.1506
$error
[1] 6.568058
$estimand
[1] "richness"
$name
[1] "wlrm_transformed"
$interval
[1] 308.4754 470.0321
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$para
Estimate Std. Error
(Intercept) 0.7809542 0.19223603
xs 0.1137681 0.01622871
$other$full
Call:
lm(formula = log(ys) ~ xs, weights = weights_trans)
Coefficients:
(Intercept) xs
0.7810 0.1138
$other$cutoff
[1] 31
$est
[1] 326.1506
$seest
[1] 6.568058
$ci
[1] 308.4754 470.0321
$estimate
[1] 17172.71
$error
[1] 25406.72
$estimand
[1] "richness"
$name
[1] "wlrm_untransformed"
$interval
[1] 2343.552 8988555.243
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$para
Estimate Std. Error
(Intercept) 0.04645303 0.07944223
xs 0.79539264 0.04466347
$other$full
Call:
lm(formula = ys ~ xs, weights = weights_untrans)
Coefficients:
(Intercept) xs
0.04645 0.79539
$other$cutoff
[1] 63
$est
[1] 17172.71
$seest
[1] 25406.72
$ci
[1] 2343.552 8988555.243
$estimate
[1] 1329.659
$error
[1] 77.00265
$estimand
[1] "richness"
$name
[1] "wlrm_untransformed"
$interval
[1] 1011.418 10517.510
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$para
Estimate Std. Error
(Intercept) 0.8402622 0.18726617
xs 0.4302112 0.07963557
$other$full
Call:
lm(formula = ys ~ xs, weights = weights_untrans)
Coefficients:
(Intercept) xs
0.8403 0.4302
$other$cutoff
[1] 33
$est
[1] 1329.659
$seest
[1] 77.00265
$ci
[1] 1011.418 10517.510
$estimate
[1] 454.3961
$error
[1] 90.41193
$estimand
[1] "richness"
$name
[1] "wlrm_untransformed"
$interval
[1] 333.2136 7209.7238
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$para
Estimate Std. Error
(Intercept) 0.3565752 0.2549538
xs 0.4224995 0.1016797
$other$full
Call:
lm(formula = ys ~ xs, weights = weights_untrans)
Coefficients:
(Intercept) xs
0.3566 0.4225
$other$cutoff
[1] 28
$est
[1] 454.3961
$seest
[1] 90.41193
$ci
[1] 333.2136 7209.7238
$estimate
[1] 370.9951
$error
[1] 7.278956
$estimand
[1] "richness"
$name
[1] "wlrm_untransformed"
$interval
[1] 357.3472 522.8973
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$para
Estimate Std. Error
(Intercept) 1.3337724 0.4705246
xs 0.5083045 0.1057248
$other$full
Call:
lm(formula = ys ~ xs, weights = weights_untrans)
Coefficients:
(Intercept) xs
1.3338 0.5083
$other$cutoff
[1] 26
$est
[1] 370.9951
$seest
[1] 7.278956
$ci
[1] 357.3472 522.8973
$estimate
[1] 377.421
$error
[1] 10.02023
$estimand
[1] "richness"
$name
[1] "wlrm_untransformed"
$interval
[1] 351.5538 665.2963
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$para
Estimate Std. Error
(Intercept) 1.2314857 0.31651827
xs 0.3904014 0.07329653
$other$full
Call:
lm(formula = ys ~ xs, weights = weights_untrans)
Coefficients:
(Intercept) xs
1.2315 0.3904
$other$cutoff
[1] 41
$est
[1] 377.421
$seest
[1] 10.02023
$ci
[1] 351.5538 665.2963
$estimate
[1] 385.6043
$error
[1] 7.22905
$estimand
[1] "richness"
$name
[1] "wlrm_untransformed"
$interval
[1] 368.9285 546.4727
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$para
Estimate Std. Error
(Intercept) 1.4512764 0.37146900
xs 0.4437526 0.08545767
$other$full
Call:
lm(formula = ys ~ xs, weights = weights_untrans)
Coefficients:
(Intercept) xs
1.4513 0.4438
$other$cutoff
[1] 34
$est
[1] 385.6043
$seest
[1] 7.22905
$ci
[1] 368.9285 546.4727
$estimate
[1] 450.7536
$error
[1] 109.5887
$estimand
[1] "richness"
$name
[1] "wlrm_untransformed"
$interval
[1] 308.3385 9266.2155
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Negative Binomial"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$para
Estimate Std. Error
(Intercept) 0.3039649 0.22522282
xs 0.6353653 0.08851121
$other$full
Call:
lm(formula = ys ~ xs, weights = weights_untrans)
Coefficients:
(Intercept) xs
0.3040 0.6354
$other$cutoff
[1] 31
$est
[1] 450.7536
$seest
[1] 109.5887
$ci
[1] 308.3385 9266.2155
$estimate
[1] 3177.141
$error
[1] 88.21714
$estimand
[1] "richness"
$name
[1] "chao1_bc"
$interval
[1] 2362.649 19189.923
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 3177.141
$seest
[1] 88.21714
$ci
[1] 2362.649 19189.923
$estimate
[1] 1238.912
$error
[1] 37.69171
$estimand
[1] "richness"
$name
[1] "chao1_bc"
$interval
[1] 1015.602 4658.503
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 1238.912
$seest
[1] 37.69171
$ci
[1] 1015.602 4658.503
$estimate
[1] 368.84
$error
[1] 15.03456
$estimand
[1] "richness"
$name
[1] "chao1_bc"
$interval
[1] 333.4643 912.0415
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 368.84
$seest
[1] 15.03456
$ci
[1] 333.4643 912.0415
$estimate
[1] 366.5556
$error
[1] 6.314576
$estimand
[1] "richness"
$name
[1] "chao1_bc"
$interval
[1] 356.9099 478.4579
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 366.5556
$seest
[1] 6.314576
$ci
[1] 356.9099 478.4579
$estimate
[1] 369.5172
$error
[1] 9.168819
$estimand
[1] "richness"
$name
[1] "chao1_bc"
$interval
[1] 350.6818 599.2976
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 369.5172
$seest
[1] 9.168819
$ci
[1] 350.6818 599.2976
$estimate
[1] 380
$error
[1] 6.710938
$estimand
[1] "richness"
$name
[1] "chao1_bc"
$interval
[1] 368.1824 509.9289
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 380
$seest
[1] 6.710938
$ci
[1] 368.1824 509.9289
$estimate
[1] 358.5556
$error
[1] 21.31788
$estimand
[1] "richness"
$name
[1] "chao1_bc"
$interval
[1] 308.7484 1310.9893
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson (homogeneous)"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
NULL
$est
[1] 358.5556
$seest
[1] 21.31788
$ci
[1] 308.7484 1310.9893
$estimate
[1] 3099.945
$error
[1] 2944.04
$estimand
[1] "richness"
$name
[1] "breakaway_nof1"
$interval
beta0 beta0
1631.675 363345.520
$interval_type
[1] "Approximate: log-normal"
$type
NULL
$model
[1] "Kemp"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] TRUE
$other
$other$xbar
[1] 31.5
$other$code
[1] 1
$other$the_function
[1] "f_{x+1}/f_{x} ~ (beta0+beta1*(x-xbar))/(1+alpha1*(x-xbar))"
$other$name
[1] "model_1_1"
$est
[1] 3099.945
$seest
[1] 2944.04
$ci
beta0 beta0
1631.675 363345.520
$para
Coef estimates Coef std errors
beta0 1.20274114 0.15475350
beta1 0.03355936 0.01238761
alpha1 0.02241446 0.01614515
$full
Nonlinear regression model
model: y ~ structure_1_1(x, beta0, beta1, alpha1)
data: lhs
beta0 beta1 alpha1
1.20274 0.03356 0.02241
weighted residual sum-of-squares: 2.155
Number of iterations to convergence: 5
Achieved convergence tolerance: 3.274e-06
$estimate
[1] 1500.401
$error
[1] 1341.351
$estimand
[1] "richness"
$name
[1] "breakaway_nof1"
$interval
beta0 beta0
724.8861 139032.6457
$interval_type
[1] "Approximate: log-normal"
$type
NULL
$model
[1] "Kemp"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] TRUE
$other
$other$xbar
[1] 16.5
$other$code
[1] 1
$other$the_function
[1] "f_{x+1}/f_{x} ~ (beta0+beta1*(x-xbar))/(1+alpha1*(x-xbar))"
$other$name
[1] "model_1_1"
$est
[1] 1500.401
$seest
[1] 1341.351
$ci
beta0 beta0
724.8861 139032.6457
$para
Coef estimates Coef std errors
beta0 1.20078845 0.18102489
beta1 0.05614293 0.04800126
alpha1 0.02874888 0.05381204
$full
Nonlinear regression model
model: y ~ structure_1_1(x, beta0, beta1, alpha1)
data: lhs
beta0 beta1 alpha1
1.20079 0.05614 0.02875
weighted residual sum-of-squares: 1.274
Number of iterations to convergence: 25
Achieved convergence tolerance: 8.431e-06
$estimate
[1] 131.0542
$error
[1] 0.06962563
$estimand
[1] "richness"
$name
[1] "PoissonModel"
$interval
[1] 131.0306 131.0962
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson"
$warnings
[1] "no kemp models converged"
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$outcome
[1] 0
$other$code
[1] 1
$est
[1] 131.0542
$seest
[1] 0.06962563
$ci
[1] 131.0306 131.0962
$estimate
[1] 181.0752
$error
[1] 0.08198957
$estimand
[1] "richness"
$name
[1] "PoissonModel"
$interval
[1] 181.0424 181.1335
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson"
$warnings
[1] "no kemp models converged"
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$outcome
[1] 0
$other$code
[1] 1
$est
[1] 181.0752
$seest
[1] 0.08198957
$ci
[1] 181.0424 181.1335
$estimate
[1] 226.0025
$error
[1] 0.01296301
$estimand
[1] "richness"
$name
[1] "PoissonModel"
$interval
[1] 226.0015 226.0042
$interval_type
[1] "Approximate: log-normal"
$type
[1] "parametric"
$model
[1] "Poisson"
$warnings
[1] "no kemp models converged"
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] FALSE
$other
$other$outcome
[1] 0
$other$code
[1] 1
$est
[1] 226.0025
$seest
[1] 0.01296301
$ci
[1] 226.0015 226.0042
$estimate
[1] 438.3885
$error
[1] 170.5326
$estimand
[1] "richness"
$name
[1] "breakaway_nof1"
$interval
beta0 beta0
340.4654 8249.2646
$interval_type
[1] "Approximate: log-normal"
$type
NULL
$model
[1] "Kemp"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] TRUE
$other
$other$xbar
[1] 17
$other$code
[1] 1
$other$the_function
[1] "f_{x+1}/f_{x} ~ (beta0+beta1*(x-xbar))/(1+alpha1*(x-xbar))"
$other$name
[1] "model_1_1"
$est
[1] 438.3885
$seest
[1] 170.5326
$ci
beta0 beta0
340.4654 8249.2646
$para
Coef estimates Coef std errors
beta0 1.37045876 0.22197453
beta1 0.05764483 0.06192103
alpha1 0.02187070 0.05307755
$full
Nonlinear regression model
model: y ~ structure_1_1(x, beta0, beta1, alpha1)
data: lhs
beta0 beta1 alpha1
1.37046 0.05764 0.02187
weighted residual sum-of-squares: 334.7
Number of iterations to convergence: 4
Achieved convergence tolerance: 2.52e-06
$estimate
[1] 293.0844
$error
[1] 7.454846
$estimand
[1] "richness"
$name
[1] "breakaway_nof1"
$interval
beta0 beta0
263.3197 434.2805
$interval_type
[1] "Approximate: log-normal"
$type
NULL
$model
[1] "Kemp"
$warnings
NULL
$frequentist
[1] TRUE
$parametric
[1] TRUE
$reasonable
[1] TRUE
$other
$other$xbar
[1] 15.5
$other$code
[1] 1
$other$the_function
[1] "f_{x+1}/f_{x} ~ (beta0+beta1*(x-xbar))/(1+alpha1*(x-xbar))"
$other$name
[1] "model_1_1"
$est
[1] 293.0844
$seest
[1] 7.454846
$ci
beta0 beta0
263.3197 434.2805
$para
Coef estimates Coef std errors
beta0 1.07899737 0.130652854
beta1 -0.07078637 0.014271665
alpha1 -0.06774517 0.003805578
$full
Nonlinear regression model
model: y ~ structure_1_1(x, beta0, beta1, alpha1)
data: lhs
beta0 beta1 alpha1
1.07900 -0.07079 -0.06775
weighted residual sum-of-squares: 1.312
Number of iterations to convergence: 18
Achieved convergence tolerance: 6.196e-06
Estimate of richness from method breakaway:
Estimate is 1552
with standard error 304.71
Confidence interval: (1007, 47805)
[ FAIL 1 | WARN 1 | SKIP 0 | PASS 254 ]
== Failed tests ================================================================
-- Error ('test-q2.R:6'): Canonical QIIME2 Example Datasets Work ---------------
<SSL_CONNECT_ERROR/GenericCurlError/error/condition>
Error in `function (type, msg, asError = TRUE)
{
if (!is.character(type)) {
i = match(type, CURLcodeValues)
typeName = if (is.na(i))
character()
else names(CURLcodeValues)[i]
}
typeName = gsub("^CURLE_", "", typeName)
fun = (if (asError)
stop
else warning)
fun(structure(list(message = msg, call = sys.call()), class = c(typeName,
"GenericCurlError", "error", "condition")))
}(35L, "error:1407742E:SSL routines:SSL23_GET_SERVER_HELLO:tlsv1 alert protocol version",
TRUE)`: error:1407742E:SSL routines:SSL23_GET_SERVER_HELLO:tlsv1 alert protocol version
Backtrace:
x
1. +-RCurl::getURL("https://raw.githubusercontent.com/paulinetrinh/data/master/otu_table_atacama.txt") at test-q2.R:6:2
2. | \-RCurl::curlPerform(curl = curl, .opts = opts, .encoding = .encoding)
3. \-RCurl (local) `<fn>`(...)
[ FAIL 1 | WARN 1 | SKIP 0 | PASS 254 ]
Error: Test failures
Execution halted
Flavor: r-oldrel-windows-ix86+x86_64
Version: 4.8.2
Check: re-building of vignette outputs
Result: WARN
Error(s) in re-building vignettes:
--- re-building 'breakaway.Rmd' using rmarkdown
frequency
71 1
index
71 2922
--- finished re-building 'breakaway.Rmd'
--- re-building 'diversity-hypothesis-testing.Rmd' using rmarkdown
Error: processing vignette 'diversity-hypothesis-testing.Rmd' failed with diagnostics:
object 'preview_math' not found
--- failed re-building 'diversity-hypothesis-testing.Rmd'
--- re-building 'intro-diversity-estimation.Rmd' using rmarkdown
Error: processing vignette 'intro-diversity-estimation.Rmd' failed with diagnostics:
object 'preview_math' not found
--- failed re-building 'intro-diversity-estimation.Rmd'
SUMMARY: processing the following files failed:
'diversity-hypothesis-testing.Rmd' 'intro-diversity-estimation.Rmd'
Error: Vignette re-building failed.
Execution halted
Flavor: r-oldrel-windows-ix86+x86_64