CRAN Package Check Results for Package SimRepeat

Last updated on 2019-12-21 10:48:00 CET.

Check Details

Version: 0.1.0
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building 'Corr_Cont_System.Rmd' using rmarkdown
    Loading required package: SimMultiCorrData
    
    Attaching package: 'SimMultiCorrData'
    
    The following object is masked from 'package:stats':
    
     poly
    
    Loading required package: SimCorrMix
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
    :
     --- package (from environment) ---
    SimRepeat
     --- call from context ---
    checkpar(M, method, error_type, means, vars, skews, skurts, fifths,
     sixths, Six, mix_pis, mix_mus, mix_sigmas, mix_skews, mix_skurts,
     mix_fifths, mix_sixths, mix_Six, same.var = same.var, betas.0 = betas.0,
     corr.x = corr.x, corr.yx = corr.yx, corr.e = corr.e, quiet = TRUE)
     --- call from argument ---
    if (class(same.var) == "matrix") {
     if (ncol(same.var) != 4)
     stop("same.var should be matrix with 4 columns.")
    } else if (class(same.var) == "numeric") {
     if (length(same.var) > ncol(corr.x[[1]][[1]]))
     stop("same.var should be vector with at most ncol(corr.x[[1]][[1]])\n elements.")
    } else stop("same.var should be vector or matrix.")
     --- R stacktrace ---
    where 1: checkpar(M, method, error_type, means, vars, skews, skurts, fifths,
     sixths, Six, mix_pis, mix_mus, mix_sigmas, mix_skews, mix_skurts,
     mix_fifths, mix_sixths, mix_Six, same.var = same.var, betas.0 = betas.0,
     corr.x = corr.x, corr.yx = corr.yx, corr.e = corr.e, quiet = TRUE)
    where 2: eval(expr, envir, enclos)
    where 3: eval(expr, envir, enclos)
    where 4: withVisible(eval(expr, envir, enclos))
    where 5: withCallingHandlers(withVisible(eval(expr, envir, enclos)), warning = wHandler,
     error = eHandler, message = mHandler)
    where 6: handle(ev <- withCallingHandlers(withVisible(eval(expr, envir,
     enclos)), warning = wHandler, error = eHandler, message = mHandler))
    where 7: timing_fn(handle(ev <- withCallingHandlers(withVisible(eval(expr,
     envir, enclos)), warning = wHandler, error = eHandler, message = mHandler)))
    where 8: evaluate_call(expr, parsed$src[[i]], envir = envir, enclos = enclos,
     debug = debug, last = i == length(out), use_try = stop_on_error !=
     2L, keep_warning = keep_warning, keep_message = keep_message,
     output_handler = output_handler, include_timing = include_timing)
    where 9: evaluate::evaluate(...)
    where 10: evaluate(code, envir = env, new_device = FALSE, keep_warning = !isFALSE(options$warning),
     keep_message = !isFALSE(options$message), stop_on_error = if (options$error &&
     options$include) 0L else 2L, output_handler = knit_handlers(options$render,
     options))
    where 11: in_dir(input_dir(), evaluate(code, envir = env, new_device = FALSE,
     keep_warning = !isFALSE(options$warning), keep_message = !isFALSE(options$message),
     stop_on_error = if (options$error && options$include) 0L else 2L,
     output_handler = knit_handlers(options$render, options)))
    where 12: block_exec(params)
    where 13: call_block(x)
    where 14: process_group.block(group)
    where 15: process_group(group)
    where 16: withCallingHandlers(if (tangle) process_tangle(group) else process_group(group),
     error = function(e) {
     setwd(wd)
     cat(res, sep = "\n", file = output %n% "")
     message("Quitting from lines ", paste(current_lines(i),
     collapse = "-"), " (", knit_concord$get("infile"),
     ") ")
     })
    where 17: process_file(text, output)
    where 18: knitr::knit(knit_input, knit_output, envir = envir, quiet = quiet)
    where 19: rmarkdown::render(file, encoding = encoding, quiet = quiet, envir = globalenv(),
     ...)
    where 20: vweave_rmarkdown(...)
    where 21: engine$weave(file, quiet = quiet, encoding = enc)
    where 22: doTryCatch(return(expr), name, parentenv, handler)
    where 23: tryCatchOne(expr, names, parentenv, handlers[[1L]])
    where 24: tryCatchList(expr, classes, parentenv, handlers)
    where 25: tryCatch({
     engine$weave(file, quiet = quiet, encoding = enc)
     setwd(startdir)
     output <- find_vignette_product(name, by = "weave", engine = engine)
     if (!have.makefile && vignette_is_tex(output)) {
     texi2pdf(file = output, clean = FALSE, quiet = quiet)
     output <- find_vignette_product(name, by = "texi2pdf",
     engine = engine)
     }
    }, error = function(e) {
     OK <<- FALSE
     message(gettextf("Error: processing vignette '%s' failed with diagnostics:\n%s",
     file, conditionMessage(e)))
    })
    where 26: tools:::.buildOneVignette("Corr_Cont_System.Rmd", "/home/hornik/tmp/R.check/r-devel-clang/Work/PKGS/SimRepeat.Rcheck/vign_test/SimRepeat",
     TRUE, FALSE, "Corr_Cont_System", "UTF-8", "/tmp/Rtmp4qvEIV/file5922651ce0b6.rds")
    
     --- value of length: 2 type: logical ---
    [1] TRUE FALSE
     --- function from context ---
    function (M = NULL, method = c("Fleishman", "Polynomial"), error_type = c("non_mix",
     "mix"), means = list(), vars = list(), skews = list(), skurts = list(),
     fifths = list(), sixths = list(), Six = list(), mix_pis = list(),
     mix_mus = list(), mix_sigmas = list(), mix_skews = list(),
     mix_skurts = list(), mix_fifths = list(), mix_sixths = list(),
     mix_Six = list(), marginal = list(), support = list(), lam = list(),
     p_zip = list(), pois_eps = list(), size = list(), prob = list(),
     mu = list(), p_zinb = list(), nb_eps = list(), corr.x = list(),
     corr.yx = list(), corr.e = NULL, same.var = NULL, subj.var = NULL,
     int.var = NULL, tint.var = NULL, betas.0 = NULL, betas = list(),
     betas.subj = list(), betas.int = list(), betas.t = NULL,
     betas.tint = list(), rand.int = c("none", "non_mix", "mix"),
     rand.tsl = c("none", "non_mix", "mix"), rand.var = NULL,
     corr.u = list(), quiet = FALSE)
    {
     if (length(error_type) != 1)
     stop("Please choose one type of distribution for all of the error terms:\n mix if all errors have continuous mixture distributions,\n non_mix if all errors have continuous non-mixture distributions.")
     if (length(method) != 1)
     stop("Choose a PMT method for the continuous variables.")
     K.cat <- rep(0, M)
     K.pois <- rep(0, M)
     K.nb <- rep(0, M)
     if (length(marginal) > 0)
     K.cat <- lengths(marginal)
     if (max(K.cat) > 0) {
     if (!all(unlist(lapply(marginal, function(x) unlist(lapply(x,
     function(y) (sort(y) == y & min(y) > 0 & max(y) <
     1)))))))
     stop("Error in given marginal distributions.")
     if (length(support) > 0) {
     if (!all(K.cat %in% lengths(support)))
     stop("Lengths of support do not match lengths of marginal.")
     k.cat <- unlist(lapply(marginal, function(x) lengths(x) +
     1))
     k.cat2 <- unlist(lapply(support, function(x) lengths(x)))
     if (!all(mapply(function(x, y) (if (y == 0 | y ==
     x) TRUE else FALSE), k.cat, k.cat2)))
     stop("Error in given support values.")
     }
     }
     if (length(lam) > 0)
     K.pois <- lengths(lam)
     if (max(K.pois) > 0) {
     if (sum(sapply(lam, function(x) sum(x < 0)) > 0) > 0)
     stop("Lambda values cannot be negative.")
     if (class(p_zip) == "numeric" & length(p_zip) == 1 &
     quiet == FALSE) {
     message("All p_zip values will be set at p_zip.")
     }
     else if (class(p_zip) == "numeric" & length(p_zip) ==
     M & quiet == FALSE) {
     message("All p_zip[[p]] values will be set at p_zip[p].")
     }
     else if (class(p_zip) == "list" & length(p_zip) == M &
     quiet == FALSE) {
     for (p in 1:M) {
     if (length(p_zip[[p]]) != K.pois[p])
     message(paste("Missing value of p_zip for equation ",
     p, " will be set at 0.", sep = ""))
     }
     }
     else if (quiet == FALSE) {
     message("All p_zip values will be set at 0.")
     }
     if (class(pois_eps) == "numeric" & length(pois_eps) ==
     1 & quiet == FALSE) {
     message("All pois_eps values will be set at pois_eps.")
     }
     else if (class(pois_eps) == "numeric" & length(pois_eps) ==
     M & quiet == FALSE) {
     message("All pois_eps[[p]] values will be set at pois_eps[p].")
     }
     else if (class(pois_eps) == "list" & length(pois_eps) ==
     M & quiet == FALSE) {
     for (p in 1:M) {
     if (length(pois_eps[[p]]) != K.pois[p])
     message(paste("Missing value of pois_eps for equation ",
     p, " will be set at 0.0001.", sep = ""))
     }
     }
     else if (quiet == FALSE) {
     message("All pois_eps values will be set at 0.0001.")
     }
     }
     if (length(size) > 0)
     K.nb <- lengths(size)
     if (max(K.nb) > 0) {
     if (sum(sapply(size, function(x) sum(x < 0)) > 0) > 0)
     stop("Size values cannot be negative.")
     if (length(prob) > 0) {
     if (sum(sapply(prob, function(x) sum(x < 0)) > 0) >
     0)
     stop("Prob values cannot be negative.")
     if (!all(lengths(prob) %in% K.nb))
     stop("Check lengths of prob vectors.")
     }
     if (length(mu) > 0) {
     if (sum(sapply(mu, function(x) sum(x < 0)) > 0) >
     0)
     stop("mu values cannot be negative.")
     if (!all(lengths(mu) %in% K.nb))
     stop("Check lengths of mu vectors.")
     }
     if (class(p_zinb) == "numeric" & length(p_zinb) == 1 &
     quiet == FALSE) {
     message("All p_zinb values will be set at p_zinb.")
     }
     else if (class(p_zinb) == "numeric" & length(p_zinb) ==
     M & quiet == FALSE) {
     message("All p_zinb[[p]] values will be set at p_zinb[p].")
     }
     else if (class(p_zinb) == "list" & length(p_zinb) ==
     M & quiet == FALSE) {
     for (p in 1:M) {
     if (length(p_zinb[[p]]) != K.nb[p])
     message(paste("Missing value of p_zinb for equation ",
     p, " will be set at 0.", sep = ""))
     }
     }
     else if (quiet == FALSE) {
     message("All p_zinb values will be set at 0.")
     }
     if (class(nb_eps) == "numeric" & length(nb_eps) == 1 &
     quiet == FALSE) {
     message("All nb_eps values will be set at nb_eps.")
     }
     else if (class(nb_eps) == "numeric" & length(nb_eps) ==
     M & quiet == FALSE) {
     message("All nb_eps[[p]] values will be set at nb_eps[p].")
     }
     else if (class(nb_eps) == "list" & length(nb_eps) ==
     M & quiet == FALSE) {
     for (p in 1:M) {
     if (length(nb_eps[[p]]) != K.nb[p])
     message(paste("Missing value of nb_eps for equation ",
     p, " will be set at 0.0001.", sep = ""))
     }
     }
     else if (quiet == FALSE) {
     message("All nb_eps values will be set at 0.0001.")
     }
     }
     if (!(length(means) %in% c(M, 1 + M, 2 * M)) | !(length(vars) %in%
     c(M, 1 + M, 2 * M)))
     stop("Each equation must have a continuous error term with means given in\n means and variances in vars. Length of means and vars\n should be M, 1 + M, or 2 * M.")
     M0 <- length(means)
     K.mix <- rep(0, M0)
     K.comp <- rep(0, M0)
     if (length(mix_pis) > 0) {
     if (length(mix_pis) == M0) {
     K.mix <- lengths(mix_pis)
     K.comp <- lengths(lapply(mix_pis, unlist))
     }
     else {
     K.mix <- c(lengths(mix_pis), rep(0, M0 - M))
     K.comp <- c(lengths(lapply(mix_pis, unlist)), rep(0,
     M0 - M))
     }
     }
     K.cont <- lengths(vars) - K.mix
     if (!all(lengths(means) %in% (K.cont + K.mix)))
     stop("Lengths of mean vectors should be same as lengths of vars vectors.")
     if (max(K.cont) > 0) {
     if (!all(lengths(skews) %in% K.cont) | !all(lengths(skurts) %in%
     K.cont))
     stop("Lengths of continuous non-mixture lists should equal lengths of\n vars minus the number of continuous mixture variables.")
     if (method == "Polynomial") {
     if (!all(lengths(fifths) %in% K.cont) | !all(lengths(sixths) %in%
     K.cont))
     stop("Lengths of continuous non-mixture lists should equal lengths of\n vars minus the number of continuous mixture variables.")
     if (!(length(Six) %in% c(0, M, 1 + M, 2 * M)))
     stop("Six should be either list() or a list of length M, M + 1,\n or 2 * M.")
     if (length(Six) != 0) {
     for (i in 1:length(Six)) {
     if (!(length(Six[[i]]) %in% c(0, K.cont[i])))
     stop("The i-th element of Six should be either NULL or a list of\n the same length as the i-th element of sixths.")
     }
     }
     }
     }
     if (length(mix_pis) > 0) {
     if (!all(lengths(mix_mus) %in% K.mix) | !all(lengths(mix_sigmas) %in%
     K.mix) | !all(lengths(mix_skews) %in% K.mix) | !all(lengths(mix_skurts) %in%
     K.mix))
     stop("Lengths of mixing parameter lists should be equal to the number\n of mixture variables.")
     if (method == "Polynomial") {
     if (!all(lengths(mix_fifths) %in% K.mix) | !all(lengths(mix_sixths) %in%
     K.mix))
     stop("Lengths of mixing parameter lists should be equal to the number\n of mixture variables.")
     if (!(length(mix_Six) %in% c(0, M, M + 1, 2 * M)))
     stop("mix_Six should be either list() or a list of length M, M + 1,\n or 2 * M.")
     if (length(mix_Six) != 0) {
     for (i in 1:length(mix_Six)) {
     if (!(length(mix_Six[[i]]) %in% c(0, K.comp[i])))
     stop("The i-th element of mix_Six should be either NULL or a list\n of the same length as the i-th element of mix_sixths.")
     }
     }
     }
     }
     if (length(means) %in% c(2 * M, M + 1)) {
     means <- means[1:M]
     vars <- vars[1:M]
     }
     if (length(mix_pis) %in% c(2 * M, M + 1))
     mix_pis <- mix_pis[1:M]
     K.mix <- rep(0, M)
     K.comp <- rep(0, M)
     K.error <- rep(0, M)
     if (length(mix_pis) > 0) {
     K.mix <- lengths(mix_pis)
     K.comp <- sapply(lapply(mix_pis, unlist), length)
     }
     K.cont <- lengths(vars) - K.mix
     k.mix <- c(0, cumsum(K.mix))
     if (error_type == "mix") {
     K.error <- sapply(mix_pis, function(x) lengths(x[length(x)]))
     K.x <- K.cont + K.comp - K.error + K.cat + K.pois + K.nb
     K.cont2 <- K.cont
     K.mix2 <- K.mix - 1
     }
     else {
     K.x <- K.cont + K.comp - 1 + K.cat + K.pois + K.nb
     K.cont2 <- K.cont - 1
     K.mix2 <- K.mix
     }
     if (sum(lengths(means) == 0) > 0 | sum(lengths(vars) == 0) >
     0)
     stop("Each equation must have a continuous error term with means given in\n means and variances in vars.")
     if (length(corr.x) > 0) {
     if (length(corr.x) != M)
     stop("corr.x should be list of length M.")
     if (!all(lengths(corr.x) %in% c(0, M)))
     stop("corr.x should be list of lists of length M.")
     for (i in 1:M) {
     if (K.x[i] == 0)
     next
     if (!all(sapply(corr.x[[i]], function(x) if (is.null(x)) 0 else nrow(x)) %in%
     c(0, K.x[i])))
     stop("corr.x[[i]] should be list of matrices with number of rows equal\n to number of independent variables for equation i.")
     for (j in 1:M) {
     if (K.x[j] == 0)
     next
     if (ncol(corr.x[[i]][[j]]) != K.x[j])
     stop("corr.x[[i]][[j]] should be matrix with number of cols equal\n to number of independent variables for equation j.")
     }
     }
     }
     if (length(corr.yx) > 0) {
     if (length(corr.yx) != M)
     stop("corr.yx should be a list of length M.")
     if (!all(sapply(corr.yx, function(x) if (is.null(x)) 0 else nrow(x)) %in%
     c(0, 1)))
     stop("corr.yx should be a list of matrices with 1 row each.")
     if (!all(sapply(corr.yx, function(x) if (is.null(x)) 0 else ncol(x)) %in%
     K.x) & !all(sapply(corr.yx, function(x) if (is.null(x)) 0 else ncol(x)) %in%
     (K.cont2 + K.mix2)))
     stop("corr.yx should be a list of matrices with 1 row each.\n The number of columns should either equal the number of non-mixture\n plus components of mixture variables or the number of non-mixture\n plus mixture variables.")
     }
     K.r <- rep(0, M)
     if (class(corr.u) == "list" & length(corr.u) > 0) {
     K.r <- sapply(mapply("[", corr.u, lengths(corr.u), SIMPLIFY = FALSE),
     function(x) if (is.null(x))
     0
     else nrow(x[[1]]))
     if (length(corr.u) != M)
     stop("corr.u should be list of length M.")
     if (!all(lengths(corr.u) %in% c(0, M)))
     stop("corr.u should be list of lists of length M.")
     for (i in 1:M) {
     if (K.r[i] == 0)
     next
     if (!all(sapply(corr.u[[i]], function(x) if (is.null(x)) 0 else nrow(x)) %in%
     c(0, K.r[i])))
     stop("corr.u[[i]] should be list of matrices with number of rows equal\n to number of random effects for equation i.")
     for (j in 1:M) {
     if (K.r[j] == 0)
     next
     if (ncol(corr.u[[i]][[j]]) != K.r[j])
     stop("corr.u[[i]][[j]] should be matrix with number of cols equal\n to number of random effects for equation j.")
     }
     }
     }
     if (max(K.r) > 0) {
     if (length(rand.int) != M & quiet == FALSE)
     message("The random intercept for all equations will be set at\n rand.int[1].")
     if (length(rand.tsl) != M & quiet == FALSE)
     message("The random time slope for all equations will be set at\n rand.tsl[1].")
     if (!is.null(rand.var)) {
     if (ncol(rand.var) != 2)
     stop("rand.var should be matrix with 2 columns.")
     }
     }
     if (quiet == FALSE) {
     if (is.null(betas.0))
     message("The intercepts will all be set at 0.")
     if (length(betas.0) < M & length(betas.0) > 0)
     message("The intercepts will all be set at betas.0[1].")
     if (length(corr.yx) == 0 & is.null(betas.t))
     message("The time slopes will all be set at 1.")
     if (length(betas.t) < M & length(betas.t) > 0)
     message("The time slopes will all be set at betas.t[1].")
     }
     if (!is.null(same.var)) {
     if (class(same.var) == "matrix") {
     if (ncol(same.var) != 4)
     stop("same.var should be matrix with 4 columns.")
     }
     else if (class(same.var) == "numeric") {
     if (length(same.var) > ncol(corr.x[[1]][[1]]))
     stop("same.var should be vector with at most ncol(corr.x[[1]][[1]])\n elements.")
     }
     else stop("same.var should be vector or matrix.")
     }
     if (!is.null(subj.var)) {
     if (ncol(subj.var) != 2)
     stop("subj.var should be matrix with 2 columns.")
     }
     if (!is.null(int.var)) {
     if (ncol(int.var) != 3)
     stop("int.var should be matrix with 3 columns.")
     }
     if (!is.null(tint.var)) {
     if (ncol(tint.var) != 2)
     stop("tint.var should be matrix with 2 columns.")
     }
     if (length(corr.yx) == 0 & length(betas) == 0 & quiet ==
     FALSE)
     message("All betas will be set to 0 if using corrsys or corrsys2.")
     if (class(betas) == "list" & length(betas) == 1 & quiet ==
     FALSE)
     message("All betas will be set to betas[[1]].")
     if (class(betas) != "list" | (class(betas) == "list" & !(length(betas) %in%
     c(0, 1, M))))
     stop("Betas should be list of length 0, 1 or M.")
     if (length(betas.subj) == 0 & !is.null(subj.var) & quiet ==
     FALSE)
     message("All betas.subj will be set to 0 if using corrsys or corrsys2.")
     if (class(betas.subj) == "list" & length(betas.subj) == 1 &
     quiet == FALSE)
     message("All betas.subj will be set to betas.subj[[1]] if using corrsys or\n corrsys2.")
     if (class(betas.subj) != "list" | (class(betas.subj) == "list" &
     !(length(betas.subj) %in% c(0, 1, M))))
     stop("betas.subj should be list of length 0, 1 or M.")
     if (length(betas.int) == 0 & !is.null(int.var) & quiet ==
     FALSE)
     message("All betas.int will be set to 0 if using corrsys or corrsys2.")
     if (class(betas.int) == "list" & length(betas.int) == 1 &
     quiet == FALSE)
     message("All betas.int will be set to betas.int[[1]] if using corrsys or\n corrsys2.")
     if (class(betas.int) != "list" | (class(betas.int) == "list" &
     !(length(betas.int) %in% c(0, 1, M))))
     stop("betas.int should be list of length 0, 1 or M.")
     if (length(betas.tint) == 0 & !is.null(tint.var) & quiet ==
     FALSE)
     message("All betas.tint will be set to 0 if using corrsys or corrsys2.")
     if (class(betas.tint) == "list" & length(betas.tint) == 1 &
     quiet == FALSE)
     message("All betas.tint will be set to betas.tint[[1]] if using corrsys or\n corrsys2.")
     if (class(betas.tint) != "list" | (class(betas.tint) == "list" &
     !(length(betas.tint) %in% c(0, 1, M))))
     stop("betas.tint should be list of length 0, 1 or M.")
     return(TRUE)
    }
    <bytecode: 0xafdcf10>
    <environment: namespace:SimRepeat>
     --- function search by body ---
    Function checkpar in namespace SimRepeat has this body.
     ----------- END OF FAILURE REPORT --------------
    Quitting from lines 541-545 (Corr_Cont_System.Rmd)
    Error: processing vignette 'Corr_Cont_System.Rmd' failed with diagnostics:
    the condition has length > 1
    --- failed re-building 'Corr_Cont_System.Rmd'
    
    --- re-building 'Corr_MultiVarType_System.Rmd' using rmarkdown
    Loading required package: SimMultiCorrData
    
    Attaching package: 'SimMultiCorrData'
    
    The following object is masked from 'package:stats':
    
     poly
    
    Loading required package: SimCorrMix
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
    :
     --- package (from environment) ---
    SimRepeat
     --- call from context ---
    checkpar(M, method, error_type, means, vars, skews, skurts, fifths,
     sixths, Six, mix_pis, mix_mus, mix_sigmas, mix_skews, mix_skurts,
     mix_fifths, mix_sixths, mix_Six, marginal, support, lam,
     p_zip, pois_eps = list(), size, prob, mu, p_zinb, nb_eps = list(),
     corr.x, corr.yx = list(), corr.e, same.var, subj.var, int.var,
     tint.var, betas.0, betas, betas.subj, betas.int, betas.t,
     betas.tint, quiet = TRUE)
     --- call from argument ---
    if (class(same.var) == "matrix") {
     if (ncol(same.var) != 4)
     stop("same.var should be matrix with 4 columns.")
    } else if (class(same.var) == "numeric") {
     if (length(same.var) > ncol(corr.x[[1]][[1]]))
     stop("same.var should be vector with at most ncol(corr.x[[1]][[1]])\n elements.")
    } else stop("same.var should be vector or matrix.")
     --- R stacktrace ---
    where 1: checkpar(M, method, error_type, means, vars, skews, skurts, fifths,
     sixths, Six, mix_pis, mix_mus, mix_sigmas, mix_skews, mix_skurts,
     mix_fifths, mix_sixths, mix_Six, marginal, support, lam,
     p_zip, pois_eps = list(), size, prob, mu, p_zinb, nb_eps = list(),
     corr.x, corr.yx = list(), corr.e, same.var, subj.var, int.var,
     tint.var, betas.0, betas, betas.subj, betas.int, betas.t,
     betas.tint, quiet = TRUE)
    where 2: eval(expr, envir, enclos)
    where 3: eval(expr, envir, enclos)
    where 4: withVisible(eval(expr, envir, enclos))
    where 5: withCallingHandlers(withVisible(eval(expr, envir, enclos)), warning = wHandler,
     error = eHandler, message = mHandler)
    where 6: handle(ev <- withCallingHandlers(withVisible(eval(expr, envir,
     enclos)), warning = wHandler, error = eHandler, message = mHandler))
    where 7: timing_fn(handle(ev <- withCallingHandlers(withVisible(eval(expr,
     envir, enclos)), warning = wHandler, error = eHandler, message = mHandler)))
    where 8: evaluate_call(expr, parsed$src[[i]], envir = envir, enclos = enclos,
     debug = debug, last = i == length(out), use_try = stop_on_error !=
     2L, keep_warning = keep_warning, keep_message = keep_message,
     output_handler = output_handler, include_timing = include_timing)
    where 9: evaluate::evaluate(...)
    where 10: evaluate(code, envir = env, new_device = FALSE, keep_warning = !isFALSE(options$warning),
     keep_message = !isFALSE(options$message), stop_on_error = if (options$error &&
     options$include) 0L else 2L, output_handler = knit_handlers(options$render,
     options))
    where 11: in_dir(input_dir(), evaluate(code, envir = env, new_device = FALSE,
     keep_warning = !isFALSE(options$warning), keep_message = !isFALSE(options$message),
     stop_on_error = if (options$error && options$include) 0L else 2L,
     output_handler = knit_handlers(options$render, options)))
    where 12: block_exec(params)
    where 13: call_block(x)
    where 14: process_group.block(group)
    where 15: process_group(group)
    where 16: withCallingHandlers(if (tangle) process_tangle(group) else process_group(group),
     error = function(e) {
     setwd(wd)
     cat(res, sep = "\n", file = output %n% "")
     message("Quitting from lines ", paste(current_lines(i),
     collapse = "-"), " (", knit_concord$get("infile"),
     ") ")
     })
    where 17: process_file(text, output)
    where 18: knitr::knit(knit_input, knit_output, envir = envir, quiet = quiet)
    where 19: rmarkdown::render(file, encoding = encoding, quiet = quiet, envir = globalenv(),
     ...)
    where 20: vweave_rmarkdown(...)
    where 21: engine$weave(file, quiet = quiet, encoding = enc)
    where 22: doTryCatch(return(expr), name, parentenv, handler)
    where 23: tryCatchOne(expr, names, parentenv, handlers[[1L]])
    where 24: tryCatchList(expr, classes, parentenv, handlers)
    where 25: tryCatch({
     engine$weave(file, quiet = quiet, encoding = enc)
     setwd(startdir)
     output <- find_vignette_product(name, by = "weave", engine = engine)
     if (!have.makefile && vignette_is_tex(output)) {
     texi2pdf(file = output, clean = FALSE, quiet = quiet)
     output <- find_vignette_product(name, by = "texi2pdf",
     engine = engine)
     }
    }, error = function(e) {
     OK <<- FALSE
     message(gettextf("Error: processing vignette '%s' failed with diagnostics:\n%s",
     file, conditionMessage(e)))
    })
    where 26: tools:::.buildOneVignette("Corr_MultiVarType_System.Rmd", "/home/hornik/tmp/R.check/r-devel-clang/Work/PKGS/SimRepeat.Rcheck/vign_test/SimRepeat",
     TRUE, FALSE, "Corr_MultiVarType_System", "UTF-8", "/tmp/Rtmp4qvEIV/file592276ea8d98.rds")
    
     --- value of length: 2 type: logical ---
    [1] TRUE FALSE
     --- function from context ---
    function (M = NULL, method = c("Fleishman", "Polynomial"), error_type = c("non_mix",
     "mix"), means = list(), vars = list(), skews = list(), skurts = list(),
     fifths = list(), sixths = list(), Six = list(), mix_pis = list(),
     mix_mus = list(), mix_sigmas = list(), mix_skews = list(),
     mix_skurts = list(), mix_fifths = list(), mix_sixths = list(),
     mix_Six = list(), marginal = list(), support = list(), lam = list(),
     p_zip = list(), pois_eps = list(), size = list(), prob = list(),
     mu = list(), p_zinb = list(), nb_eps = list(), corr.x = list(),
     corr.yx = list(), corr.e = NULL, same.var = NULL, subj.var = NULL,
     int.var = NULL, tint.var = NULL, betas.0 = NULL, betas = list(),
     betas.subj = list(), betas.int = list(), betas.t = NULL,
     betas.tint = list(), rand.int = c("none", "non_mix", "mix"),
     rand.tsl = c("none", "non_mix", "mix"), rand.var = NULL,
     corr.u = list(), quiet = FALSE)
    {
     if (length(error_type) != 1)
     stop("Please choose one type of distribution for all of the error terms:\n mix if all errors have continuous mixture distributions,\n non_mix if all errors have continuous non-mixture distributions.")
     if (length(method) != 1)
     stop("Choose a PMT method for the continuous variables.")
     K.cat <- rep(0, M)
     K.pois <- rep(0, M)
     K.nb <- rep(0, M)
     if (length(marginal) > 0)
     K.cat <- lengths(marginal)
     if (max(K.cat) > 0) {
     if (!all(unlist(lapply(marginal, function(x) unlist(lapply(x,
     function(y) (sort(y) == y & min(y) > 0 & max(y) <
     1)))))))
     stop("Error in given marginal distributions.")
     if (length(support) > 0) {
     if (!all(K.cat %in% lengths(support)))
     stop("Lengths of support do not match lengths of marginal.")
     k.cat <- unlist(lapply(marginal, function(x) lengths(x) +
     1))
     k.cat2 <- unlist(lapply(support, function(x) lengths(x)))
     if (!all(mapply(function(x, y) (if (y == 0 | y ==
     x) TRUE else FALSE), k.cat, k.cat2)))
     stop("Error in given support values.")
     }
     }
     if (length(lam) > 0)
     K.pois <- lengths(lam)
     if (max(K.pois) > 0) {
     if (sum(sapply(lam, function(x) sum(x < 0)) > 0) > 0)
     stop("Lambda values cannot be negative.")
     if (class(p_zip) == "numeric" & length(p_zip) == 1 &
     quiet == FALSE) {
     message("All p_zip values will be set at p_zip.")
     }
     else if (class(p_zip) == "numeric" & length(p_zip) ==
     M & quiet == FALSE) {
     message("All p_zip[[p]] values will be set at p_zip[p].")
     }
     else if (class(p_zip) == "list" & length(p_zip) == M &
     quiet == FALSE) {
     for (p in 1:M) {
     if (length(p_zip[[p]]) != K.pois[p])
     message(paste("Missing value of p_zip for equation ",
     p, " will be set at 0.", sep = ""))
     }
     }
     else if (quiet == FALSE) {
     message("All p_zip values will be set at 0.")
     }
     if (class(pois_eps) == "numeric" & length(pois_eps) ==
     1 & quiet == FALSE) {
     message("All pois_eps values will be set at pois_eps.")
     }
     else if (class(pois_eps) == "numeric" & length(pois_eps) ==
     M & quiet == FALSE) {
     message("All pois_eps[[p]] values will be set at pois_eps[p].")
     }
     else if (class(pois_eps) == "list" & length(pois_eps) ==
     M & quiet == FALSE) {
     for (p in 1:M) {
     if (length(pois_eps[[p]]) != K.pois[p])
     message(paste("Missing value of pois_eps for equation ",
     p, " will be set at 0.0001.", sep = ""))
     }
     }
     else if (quiet == FALSE) {
     message("All pois_eps values will be set at 0.0001.")
     }
     }
     if (length(size) > 0)
     K.nb <- lengths(size)
     if (max(K.nb) > 0) {
     if (sum(sapply(size, function(x) sum(x < 0)) > 0) > 0)
     stop("Size values cannot be negative.")
     if (length(prob) > 0) {
     if (sum(sapply(prob, function(x) sum(x < 0)) > 0) >
     0)
     stop("Prob values cannot be negative.")
     if (!all(lengths(prob) %in% K.nb))
     stop("Check lengths of prob vectors.")
     }
     if (length(mu) > 0) {
     if (sum(sapply(mu, function(x) sum(x < 0)) > 0) >
     0)
     stop("mu values cannot be negative.")
     if (!all(lengths(mu) %in% K.nb))
     stop("Check lengths of mu vectors.")
     }
     if (class(p_zinb) == "numeric" & length(p_zinb) == 1 &
     quiet == FALSE) {
     message("All p_zinb values will be set at p_zinb.")
     }
     else if (class(p_zinb) == "numeric" & length(p_zinb) ==
     M & quiet == FALSE) {
     message("All p_zinb[[p]] values will be set at p_zinb[p].")
     }
     else if (class(p_zinb) == "list" & length(p_zinb) ==
     M & quiet == FALSE) {
     for (p in 1:M) {
     if (length(p_zinb[[p]]) != K.nb[p])
     message(paste("Missing value of p_zinb for equation ",
     p, " will be set at 0.", sep = ""))
     }
     }
     else if (quiet == FALSE) {
     message("All p_zinb values will be set at 0.")
     }
     if (class(nb_eps) == "numeric" & length(nb_eps) == 1 &
     quiet == FALSE) {
     message("All nb_eps values will be set at nb_eps.")
     }
     else if (class(nb_eps) == "numeric" & length(nb_eps) ==
     M & quiet == FALSE) {
     message("All nb_eps[[p]] values will be set at nb_eps[p].")
     }
     else if (class(nb_eps) == "list" & length(nb_eps) ==
     M & quiet == FALSE) {
     for (p in 1:M) {
     if (length(nb_eps[[p]]) != K.nb[p])
     message(paste("Missing value of nb_eps for equation ",
     p, " will be set at 0.0001.", sep = ""))
     }
     }
     else if (quiet == FALSE) {
     message("All nb_eps values will be set at 0.0001.")
     }
     }
     if (!(length(means) %in% c(M, 1 + M, 2 * M)) | !(length(vars) %in%
     c(M, 1 + M, 2 * M)))
     stop("Each equation must have a continuous error term with means given in\n means and variances in vars. Length of means and vars\n should be M, 1 + M, or 2 * M.")
     M0 <- length(means)
     K.mix <- rep(0, M0)
     K.comp <- rep(0, M0)
     if (length(mix_pis) > 0) {
     if (length(mix_pis) == M0) {
     K.mix <- lengths(mix_pis)
     K.comp <- lengths(lapply(mix_pis, unlist))
     }
     else {
     K.mix <- c(lengths(mix_pis), rep(0, M0 - M))
     K.comp <- c(lengths(lapply(mix_pis, unlist)), rep(0,
     M0 - M))
     }
     }
     K.cont <- lengths(vars) - K.mix
     if (!all(lengths(means) %in% (K.cont + K.mix)))
     stop("Lengths of mean vectors should be same as lengths of vars vectors.")
     if (max(K.cont) > 0) {
     if (!all(lengths(skews) %in% K.cont) | !all(lengths(skurts) %in%
     K.cont))
     stop("Lengths of continuous non-mixture lists should equal lengths of\n vars minus the number of continuous mixture variables.")
     if (method == "Polynomial") {
     if (!all(lengths(fifths) %in% K.cont) | !all(lengths(sixths) %in%
     K.cont))
     stop("Lengths of continuous non-mixture lists should equal lengths of\n vars minus the number of continuous mixture variables.")
     if (!(length(Six) %in% c(0, M, 1 + M, 2 * M)))
     stop("Six should be either list() or a list of length M, M + 1,\n or 2 * M.")
     if (length(Six) != 0) {
     for (i in 1:length(Six)) {
     if (!(length(Six[[i]]) %in% c(0, K.cont[i])))
     stop("The i-th element of Six should be either NULL or a list of\n the same length as the i-th element of sixths.")
     }
     }
     }
     }
     if (length(mix_pis) > 0) {
     if (!all(lengths(mix_mus) %in% K.mix) | !all(lengths(mix_sigmas) %in%
     K.mix) | !all(lengths(mix_skews) %in% K.mix) | !all(lengths(mix_skurts) %in%
     K.mix))
     stop("Lengths of mixing parameter lists should be equal to the number\n of mixture variables.")
     if (method == "Polynomial") {
     if (!all(lengths(mix_fifths) %in% K.mix) | !all(lengths(mix_sixths) %in%
     K.mix))
     stop("Lengths of mixing parameter lists should be equal to the number\n of mixture variables.")
     if (!(length(mix_Six) %in% c(0, M, M + 1, 2 * M)))
     stop("mix_Six should be either list() or a list of length M, M + 1,\n or 2 * M.")
     if (length(mix_Six) != 0) {
     for (i in 1:length(mix_Six)) {
     if (!(length(mix_Six[[i]]) %in% c(0, K.comp[i])))
     stop("The i-th element of mix_Six should be either NULL or a list\n of the same length as the i-th element of mix_sixths.")
     }
     }
     }
     }
     if (length(means) %in% c(2 * M, M + 1)) {
     means <- means[1:M]
     vars <- vars[1:M]
     }
     if (length(mix_pis) %in% c(2 * M, M + 1))
     mix_pis <- mix_pis[1:M]
     K.mix <- rep(0, M)
     K.comp <- rep(0, M)
     K.error <- rep(0, M)
     if (length(mix_pis) > 0) {
     K.mix <- lengths(mix_pis)
     K.comp <- sapply(lapply(mix_pis, unlist), length)
     }
     K.cont <- lengths(vars) - K.mix
     k.mix <- c(0, cumsum(K.mix))
     if (error_type == "mix") {
     K.error <- sapply(mix_pis, function(x) lengths(x[length(x)]))
     K.x <- K.cont + K.comp - K.error + K.cat + K.pois + K.nb
     K.cont2 <- K.cont
     K.mix2 <- K.mix - 1
     }
     else {
     K.x <- K.cont + K.comp - 1 + K.cat + K.pois + K.nb
     K.cont2 <- K.cont - 1
     K.mix2 <- K.mix
     }
     if (sum(lengths(means) == 0) > 0 | sum(lengths(vars) == 0) >
     0)
     stop("Each equation must have a continuous error term with means given in\n means and variances in vars.")
     if (length(corr.x) > 0) {
     if (length(corr.x) != M)
     stop("corr.x should be list of length M.")
     if (!all(lengths(corr.x) %in% c(0, M)))
     stop("corr.x should be list of lists of length M.")
     for (i in 1:M) {
     if (K.x[i] == 0)
     next
     if (!all(sapply(corr.x[[i]], function(x) if (is.null(x)) 0 else nrow(x)) %in%
     c(0, K.x[i])))
     stop("corr.x[[i]] should be list of matrices with number of rows equal\n to number of independent variables for equation i.")
     for (j in 1:M) {
     if (K.x[j] == 0)
     next
     if (ncol(corr.x[[i]][[j]]) != K.x[j])
     stop("corr.x[[i]][[j]] should be matrix with number of cols equal\n to number of independent variables for equation j.")
     }
     }
     }
     if (length(corr.yx) > 0) {
     if (length(corr.yx) != M)
     stop("corr.yx should be a list of length M.")
     if (!all(sapply(corr.yx, function(x) if (is.null(x)) 0 else nrow(x)) %in%
     c(0, 1)))
     stop("corr.yx should be a list of matrices with 1 row each.")
     if (!all(sapply(corr.yx, function(x) if (is.null(x)) 0 else ncol(x)) %in%
     K.x) & !all(sapply(corr.yx, function(x) if (is.null(x)) 0 else ncol(x)) %in%
     (K.cont2 + K.mix2)))
     stop("corr.yx should be a list of matrices with 1 row each.\n The number of columns should either equal the number of non-mixture\n plus components of mixture variables or the number of non-mixture\n plus mixture variables.")
     }
     K.r <- rep(0, M)
     if (class(corr.u) == "list" & length(corr.u) > 0) {
     K.r <- sapply(mapply("[", corr.u, lengths(corr.u), SIMPLIFY = FALSE),
     function(x) if (is.null(x))
     0
     else nrow(x[[1]]))
     if (length(corr.u) != M)
     stop("corr.u should be list of length M.")
     if (!all(lengths(corr.u) %in% c(0, M)))
     stop("corr.u should be list of lists of length M.")
     for (i in 1:M) {
     if (K.r[i] == 0)
     next
     if (!all(sapply(corr.u[[i]], function(x) if (is.null(x)) 0 else nrow(x)) %in%
     c(0, K.r[i])))
     stop("corr.u[[i]] should be list of matrices with number of rows equal\n to number of random effects for equation i.")
     for (j in 1:M) {
     if (K.r[j] == 0)
     next
     if (ncol(corr.u[[i]][[j]]) != K.r[j])
     stop("corr.u[[i]][[j]] should be matrix with number of cols equal\n to number of random effects for equation j.")
     }
     }
     }
     if (max(K.r) > 0) {
     if (length(rand.int) != M & quiet == FALSE)
     message("The random intercept for all equations will be set at\n rand.int[1].")
     if (length(rand.tsl) != M & quiet == FALSE)
     message("The random time slope for all equations will be set at\n rand.tsl[1].")
     if (!is.null(rand.var)) {
     if (ncol(rand.var) != 2)
     stop("rand.var should be matrix with 2 columns.")
     }
     }
     if (quiet == FALSE) {
     if (is.null(betas.0))
     message("The intercepts will all be set at 0.")
     if (length(betas.0) < M & length(betas.0) > 0)
     message("The intercepts will all be set at betas.0[1].")
     if (length(corr.yx) == 0 & is.null(betas.t))
     message("The time slopes will all be set at 1.")
     if (length(betas.t) < M & length(betas.t) > 0)
     message("The time slopes will all be set at betas.t[1].")
     }
     if (!is.null(same.var)) {
     if (class(same.var) == "matrix") {
     if (ncol(same.var) != 4)
     stop("same.var should be matrix with 4 columns.")
     }
     else if (class(same.var) == "numeric") {
     if (length(same.var) > ncol(corr.x[[1]][[1]]))
     stop("same.var should be vector with at most ncol(corr.x[[1]][[1]])\n elements.")
     }
     else stop("same.var should be vector or matrix.")
     }
     if (!is.null(subj.var)) {
     if (ncol(subj.var) != 2)
     stop("subj.var should be matrix with 2 columns.")
     }
     if (!is.null(int.var)) {
     if (ncol(int.var) != 3)
     stop("int.var should be matrix with 3 columns.")
     }
     if (!is.null(tint.var)) {
     if (ncol(tint.var) != 2)
     stop("tint.var should be matrix with 2 columns.")
     }
     if (length(corr.yx) == 0 & length(betas) == 0 & quiet ==
     FALSE)
     message("All betas will be set to 0 if using corrsys or corrsys2.")
     if (class(betas) == "list" & length(betas) == 1 & quiet ==
     FALSE)
     message("All betas will be set to betas[[1]].")
     if (class(betas) != "list" | (class(betas) == "list" & !(length(betas) %in%
     c(0, 1, M))))
     stop("Betas should be list of length 0, 1 or M.")
     if (length(betas.subj) == 0 & !is.null(subj.var) & quiet ==
     FALSE)
     message("All betas.subj will be set to 0 if using corrsys or corrsys2.")
     if (class(betas.subj) == "list" & length(betas.subj) == 1 &
     quiet == FALSE)
     message("All betas.subj will be set to betas.subj[[1]] if using corrsys or\n corrsys2.")
     if (class(betas.subj) != "list" | (class(betas.subj) == "list" &
     !(length(betas.subj) %in% c(0, 1, M))))
     stop("betas.subj should be list of length 0, 1 or M.")
     if (length(betas.int) == 0 & !is.null(int.var) & quiet ==
     FALSE)
     message("All betas.int will be set to 0 if using corrsys or corrsys2.")
     if (class(betas.int) == "list" & length(betas.int) == 1 &
     quiet == FALSE)
     message("All betas.int will be set to betas.int[[1]] if using corrsys or\n corrsys2.")
     if (class(betas.int) != "list" | (class(betas.int) == "list" &
     !(length(betas.int) %in% c(0, 1, M))))
     stop("betas.int should be list of length 0, 1 or M.")
     if (length(betas.tint) == 0 & !is.null(tint.var) & quiet ==
     FALSE)
     message("All betas.tint will be set to 0 if using corrsys or corrsys2.")
     if (class(betas.tint) == "list" & length(betas.tint) == 1 &
     quiet == FALSE)
     message("All betas.tint will be set to betas.tint[[1]] if using corrsys or\n corrsys2.")
     if (class(betas.tint) != "list" | (class(betas.tint) == "list" &
     !(length(betas.tint) %in% c(0, 1, M))))
     stop("betas.tint should be list of length 0, 1 or M.")
     return(TRUE)
    }
    <bytecode: 0x97cdcb8>
    <environment: namespace:SimRepeat>
     --- function search by body ---
    Function checkpar in namespace SimRepeat has this body.
     ----------- END OF FAILURE REPORT --------------
    Quitting from lines 531-537 (Corr_MultiVarType_System.Rmd)
    Error: processing vignette 'Corr_MultiVarType_System.Rmd' failed with diagnostics:
    the condition has length > 1
    --- failed re-building 'Corr_MultiVarType_System.Rmd'
    
    --- re-building 'HLM_Approach.Rmd' using rmarkdown
    --- finished re-building 'HLM_Approach.Rmd'
    
    --- re-building 'Theory_Cont_System.Rmd' using rmarkdown
    --- finished re-building 'Theory_Cont_System.Rmd'
    
    SUMMARY: processing the following files failed:
     'Corr_Cont_System.Rmd' 'Corr_MultiVarType_System.Rmd'
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.1.0
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building ‘Corr_Cont_System.Rmd’ using rmarkdown
    Loading required package: SimMultiCorrData
    
    Attaching package: 'SimMultiCorrData'
    
    The following object is masked from 'package:stats':
    
     poly
    
    Loading required package: SimCorrMix
    Warning in if (class(same.var) == "matrix") { :
     the condition has length > 1 and only the first element will be used
    Warning in if (class(same.var) == "numeric") { :
     the condition has length > 1 and only the first element will be used
    Warning in kable_markdown(x, padding = padding, ...) :
     The table should have a header (column names)
    Warning in kable_markdown(x, padding = padding, ...) :
     The table should have a header (column names)
    --- finished re-building ‘Corr_Cont_System.Rmd’
    
    --- re-building ‘Corr_MultiVarType_System.Rmd’ using rmarkdown
    Loading required package: SimMultiCorrData
    
    Attaching package: 'SimMultiCorrData'
    
    The following object is masked from 'package:stats':
    
     poly
    
    Loading required package: SimCorrMix
    Warning in if (class(same.var) == "matrix") { :
     the condition has length > 1 and only the first element will be used
    Warning in if (class(same.var) == "numeric") { :
     the condition has length > 1 and only the first element will be used
    Warning in if (class(corr.u) == "list" & length(corr.u) > 0) { :
     the condition has length > 1 and only the first element will be used
    Warning in if (class(corr.u) == "list" & length(corr.u) > 0) K.r <- sapply(mapply("[", :
     the condition has length > 1 and only the first element will be used
    Warning in if (class(corr.u) == "matrix") K.r <- rep(ncol(corr.u), M) :
     the condition has length > 1 and only the first element will be used
    Warning in if ((class(corr.u) == "list" & length(corr.u) > 0) | class(corr.u) == :
     the condition has length > 1 and only the first element will be used
    Quitting from lines 759-765 (Corr_MultiVarType_System.Rmd)
    Error: processing vignette 'Corr_MultiVarType_System.Rmd' failed with diagnostics:
    invalid ‘times’ argument
    --- failed re-building ‘Corr_MultiVarType_System.Rmd’
    
    --- re-building ‘HLM_Approach.Rmd’ using rmarkdown
    --- finished re-building ‘HLM_Approach.Rmd’
    
    --- re-building ‘Theory_Cont_System.Rmd’ using rmarkdown
    --- finished re-building ‘Theory_Cont_System.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘Corr_MultiVarType_System.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.1.0
Check: dependencies in R code
Result: NOTE
    Namespaces in Imports field not imported from:
     ‘BB’ ‘MASS’ ‘ggplot2’ ‘grid’ ‘triangle’
     All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-solaris-x86, r-release-osx-x86_64, r-oldrel-osx-x86_64