CRAN Package Check Results for Package ordinal

Last updated on 2019-12-15 11:46:40 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 2019.4-25 17.92 219.99 237.91 ERROR
r-devel-linux-x86_64-debian-gcc 2019.4-25 16.42 179.38 195.80 OK
r-devel-linux-x86_64-fedora-clang 2019.4-25 307.41 OK
r-devel-linux-x86_64-fedora-gcc 2019.4-25 290.93 OK
r-devel-windows-ix86+x86_64 2019.4-25 31.00 480.00 511.00 OK
r-devel-windows-ix86+x86_64-gcc8 2019.4-25 39.00 475.00 514.00 OK
r-patched-linux-x86_64 2019.4-25 18.10 211.48 229.58 OK
r-patched-solaris-x86 2019.4-25 381.20 OK
r-release-linux-x86_64 2019.4-25 16.53 210.30 226.83 OK
r-release-windows-ix86+x86_64 2019.4-25 30.00 339.00 369.00 OK
r-release-osx-x86_64 2019.4-25 OK
r-oldrel-windows-ix86+x86_64 2019.4-25 29.00 336.00 365.00 OK
r-oldrel-osx-x86_64 2019.4-25 OK

Check Details

Version: 2019.4-25
Check: examples
Result: ERROR
    Running examples in 'ordinal-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: clm2
    > ### Title: Cumulative link models
    > ### Aliases: clm2
    > ### Keywords: models
    >
    > ### ** Examples
    >
    > options(contrasts = c("contr.treatment", "contr.poly"))
    >
    > ## A tabular data set:
    > (tab26 <- with(soup, table("Product" = PROD, "Response" = SURENESS)))
     Response
    Product 1 2 3 4 5 6
     Ref 132 161 65 41 121 219
     Test 96 99 50 57 156 650
    > dimnames(tab26)[[2]] <- c("Sure", "Not Sure", "Guess", "Guess", "Not Sure", "Sure")
    > dat26 <- expand.grid(sureness = as.factor(1:6), prod = c("Ref", "Test"))
    > dat26$wghts <- c(t(tab26))
    >
    > m1 <- clm2(sureness ~ prod, scale = ~prod, data = dat26,
    + weights = wghts, link = "logistic")
    >
    > ## print, summary, vcov, logLik, AIC:
    > m1
    Call:
    clm2(location = sureness ~ prod, scale = ~prod, data = dat26,
     weights = wghts, link = "logistic")
    
    Location coefficients:
    prodTest
    1.295878
    
    Scale coefficients:
     prodTest
    0.1479862
    
    Threshold coefficients:
     1|2 2|3 3|4 4|5 5|6
    -1.4912570 -0.4521846 -0.1072083 0.1633653 0.8829135
    
    log-likelihood: -2687.745
    AIC: 5389.489
    > summary(m1)
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
    :
     --- package (from environment) ---
    ordinal
     --- call from context ---
    summary.clm2(m1)
     --- call from argument ---
    if (class(vc) == "try-error") {
     warning("Variance-covariance matrix of the parameters is not defined")
     coef[, 2:4] <- NaN
     if (correlation)
     warning("Correlation matrix is unavailable")
     object$condHess <- NaN
    } else {
     coef[, 2] <- sd <- sqrt(diag(vc))
     object$condHess <- if (any(is.na(object$Hessian)))
     Inf
     else with(eigen(object$Hessian, only.values = TRUE), abs(max(values)/min(values)))
     coef[, 3] <- coef[, 1]/coef[, 2]
     coef[, 4] <- 2 * pnorm(abs(coef[, 3]), lower.tail = FALSE)
     if (correlation)
     object$correlation <- (vc/sd)/rep(sd, rep(object$edf,
     object$edf))
    }
     --- R stacktrace ---
    where 1: summary.clm2(m1)
    where 2: summary(m1)
    
     --- value of length: 2 type: logical ---
    [1] FALSE FALSE
     --- function from context ---
    function (object, digits = max(3, .Options$digits - 3), correlation = FALSE,
     ...)
    {
     if (is.null(object$Hessian))
     stop("Model needs to be fitted with Hess = TRUE")
     coef <- matrix(0, object$edf, 4, dimnames = list(names(object$coefficients),
     c("Estimate", "Std. Error", "z value", "Pr(>|z|)")))
     coef[, 1] <- object$coefficients
     vc <- try(vcov(object), silent = TRUE)
     if (class(vc) == "try-error") {
     warning("Variance-covariance matrix of the parameters is not defined")
     coef[, 2:4] <- NaN
     if (correlation)
     warning("Correlation matrix is unavailable")
     object$condHess <- NaN
     }
     else {
     coef[, 2] <- sd <- sqrt(diag(vc))
     object$condHess <- if (any(is.na(object$Hessian)))
     Inf
     else with(eigen(object$Hessian, only.values = TRUE),
     abs(max(values)/min(values)))
     coef[, 3] <- coef[, 1]/coef[, 2]
     coef[, 4] <- 2 * pnorm(abs(coef[, 3]), lower.tail = FALSE)
     if (correlation)
     object$correlation <- (vc/sd)/rep(sd, rep(object$edf,
     object$edf))
     }
     object$coefficients <- coef
     object$digits <- digits
     class(object) <- "summary.clm2"
     object
    }
    <bytecode: 0x8b15f40>
    <environment: namespace:ordinal>
     --- function search by body ---
    Function summary.clm2 in namespace ordinal has this body.
     ----------- END OF FAILURE REPORT --------------
    Error in if (class(vc) == "try-error") { : the condition has length > 1
    Calls: summary -> summary.clm2
    Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 2019.4-25
Check: tests
Result: ERROR
     Running 'anova.R' [2s/3s]
     Running 'clm.fit.R' [3s/3s]
     Running 'clm.formula.R' [3s/3s]
     Running 'clmm.R' [4s/4s]
     Running 'clmm.control.R' [2s/2s]
     Running 'clmm.formula.R' [4s/5s]
     Running 'confint.R' [4s/5s]
     Running 'nominal.test.R' [6s/7s]
     Running 'test-all.R' [28s/30s]
     Running 'test.clm.Theta.R' [4s/4s]
     Running 'test.clm.convergence.R' [3s/3s]
     Running 'test.clm.flex.link.R' [3s/4s]
     Running 'test.clm.model.matrix.R' [3s/3s]
     Running 'test.clm.predict.R' [3s/3s]
     Running 'test.clm.profile.R' [2s/3s]
     Running 'test.clm.single.anova.R' [3s/4s]
     Running 'test.general.R' [0s/1s]
     Running 'test.makeThresholds.R' [2s/3s]
     Running 'test.sign.R' [3s/4s]
     Running 'test0weights.R' [4s/4s]
     Running 'testAnova.clm2.R' [3s/3s]
     Running 'testCLM.R' [4s/4s]
    Running the tests in 'tests/clmm.R' failed.
    Complete output:
     > library(ordinal)
     > data(wine)
     >
     > #################################
     > ## Estimation with a single simple RE term:
     > ## Laplace:
     > fmm1 <- clmm(rating ~ contact + temp + (1|judge), data=wine)
     > summary(fmm1)
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
     :
     --- package (from environment) ---
     ordinal
     --- call from context ---
     summary.clmm(fmm1)
     --- call from argument ---
     if (class(vc) == "try-error") {
     warning("Variance-covariance matrix of the parameters is not defined")
     coef[, 2:4] <- NaN
     if (correlation)
     warning("Correlation matrix is unavailable")
     object$condHess <- NaN
     } else {
     coef[, 2] <- sd <- sqrt(diag(vc)[1:nfepar])
     object$condHess <- if (any(is.na(object$Hessian)))
     Inf
     else with(eigen(object$Hessian, only.values = TRUE), abs(max(values)/min(values)))
     coef[, 3] <- coef[, 1]/coef[, 2]
     coef[, 4] <- 2 * pnorm(abs(coef[, 3]), lower.tail = FALSE)
     if (correlation)
     object$correlation <- cov2cor(vc)
     }
     --- R stacktrace ---
     where 1: summary.clmm(fmm1)
     where 2: summary(fmm1)
    
     --- value of length: 2 type: logical ---
     [1] FALSE FALSE
     --- function from context ---
     function (object, correlation = FALSE, ...)
     {
     if (is.null(object$Hessian))
     stop("Model needs to be fitted with Hess = TRUE")
     nfepar <- object$dims$nfepar
     coef <- matrix(0, nfepar, 4, dimnames = list(names(object$coefficients[1:nfepar]),
     c("Estimate", "Std. Error", "z value", "Pr(>|z|)")))
     coef[, 1] <- object$coefficients[1:nfepar]
     vc <- try(vcov(object), silent = TRUE)
     if (class(vc) == "try-error") {
     warning("Variance-covariance matrix of the parameters is not defined")
     coef[, 2:4] <- NaN
     if (correlation)
     warning("Correlation matrix is unavailable")
     object$condHess <- NaN
     }
     else {
     coef[, 2] <- sd <- sqrt(diag(vc)[1:nfepar])
     object$condHess <- if (any(is.na(object$Hessian)))
     Inf
     else with(eigen(object$Hessian, only.values = TRUE),
     abs(max(values)/min(values)))
     coef[, 3] <- coef[, 1]/coef[, 2]
     coef[, 4] <- 2 * pnorm(abs(coef[, 3]), lower.tail = FALSE)
     if (correlation)
     object$correlation <- cov2cor(vc)
     }
     object$info$cond.H <- formatC(object$condHess, digits = 1,
     format = "e")
     object$coefficients <- coef
     class(object) <- "summary.clmm"
     return(object)
     }
     <bytecode: 0xaa48ed8>
     <environment: namespace:ordinal>
     --- function search by body ---
     Function summary.clmm in namespace ordinal has this body.
     ----------- END OF FAILURE REPORT --------------
     Error in if (class(vc) == "try-error") { : the condition has length > 1
     Calls: summary -> summary.clmm
     Execution halted
    Running the tests in 'tests/clmm.formula.R' failed.
    Complete output:
     > library(ordinal)
     > data(wine)
     >
     > #################################
     > ## Appropriate evaluation of formulas:
     >
     > ## These all work as intended with no warnings or errors:
     > fm1 <- clmm(rating ~ contact + (1|judge), data=wine)
     > fm1
     Cumulative Link Mixed Model fitted with the Laplace approximation
    
     formula: rating ~ contact + (1 | judge)
     data: wine
    
     link threshold nobs logLik AIC niter max.grad
     logit flexible 72 -98.80 209.59 228(686) 3.67e-06
    
     Random effects:
     Groups Name Variance Std.Dev.
     judge (Intercept) 0.4428 0.6654
     Number of groups: judge 9
    
     Coefficients:
     contactyes
     1.3
    
     Thresholds:
     1|2 2|3 3|4 4|5
     -2.28331 0.04325 1.86062 3.20298
     > fm1 <- clmm("rating ~ contact + (1|judge)", data=wine)
     > fm1
     Cumulative Link Mixed Model fitted with the Laplace approximation
    
     formula: rating ~ contact + (1 | judge)
     data: wine
    
     link threshold nobs logLik AIC niter max.grad
     logit flexible 72 -98.80 209.59 228(686) 3.67e-06
    
     Random effects:
     Groups Name Variance Std.Dev.
     judge (Intercept) 0.4428 0.6654
     Number of groups: judge 9
    
     Coefficients:
     contactyes
     1.3
    
     Thresholds:
     1|2 2|3 3|4 4|5
     -2.28331 0.04325 1.86062 3.20298
     > fm1 <- clmm(as.formula("rating ~ contact + (1|judge)"), data=wine)
     > fm1
     Cumulative Link Mixed Model fitted with the Laplace approximation
    
     formula: rating ~ contact + (1 | judge)
     data: wine
    
     link threshold nobs logLik AIC niter max.grad
     logit flexible 72 -98.80 209.59 228(686) 3.67e-06
    
     Random effects:
     Groups Name Variance Std.Dev.
     judge (Intercept) 0.4428 0.6654
     Number of groups: judge 9
    
     Coefficients:
     contactyes
     1.3
    
     Thresholds:
     1|2 2|3 3|4 4|5
     -2.28331 0.04325 1.86062 3.20298
     > fm1 <- clmm(as.formula(rating ~ contact + (1|judge)), data=wine)
     > fm1
     Cumulative Link Mixed Model fitted with the Laplace approximation
    
     formula: rating ~ contact + (1 | judge)
     data: wine
    
     link threshold nobs logLik AIC niter max.grad
     logit flexible 72 -98.80 209.59 228(686) 3.67e-06
    
     Random effects:
     Groups Name Variance Std.Dev.
     judge (Intercept) 0.4428 0.6654
     Number of groups: judge 9
    
     Coefficients:
     contactyes
     1.3
    
     Thresholds:
     1|2 2|3 3|4 4|5
     -2.28331 0.04325 1.86062 3.20298
     >
     > #################################
     >
     > ### finding variables in the environment of the formula:
     > makeform <- function() {
     + f1 <- as.formula(rating ~ temp + contact + (1|judge))
     + rating <- wine$rating
     + temp <- wine$temp
     + contact <- wine$contact
     + judge <- wine$judge
     + f1
     + }
     > ## 'makeform' makes are formula object in the environment of the
     > ## function makeform:
     > f1 <- makeform()
     > f1 # print
     rating ~ temp + contact + (1 | judge)
     <environment: 0x6f38e20>
     > class(f1)
     [1] "formula"
     > ## If we give the data, we can evaluate the model:
     > fm1 <- clmm(f1, data=wine)
     > ## We can also evaluate the model because the data are available in
     > ## the environment associated with the formula:
     > fm1 <- clmm(f1)
     > ## For instance, the 'rating' variable is not found in the Global
     > ## environment; we have to evaluate the 'name' of 'rating' in the
     > ## appropriate environment:
     > (try(rating, silent=TRUE))
     [1] "Error in try(rating, silent = TRUE) : object 'rating' not found\n"
     attr(,"class")
     [1] "try-error"
     attr(,"condition")
     <simpleError in doTryCatch(return(expr), name, parentenv, handler): object 'rating' not found>
     > eval(as.name("rating"), envir=environment(f1))
     [1] 2 3 3 4 4 4 5 5 1 2 1 3 2 3 5 4 2 3 3 2 5 5 4 4 3 2 3 2 3 2 5 3 2 3 4 3 3 3
     [39] 3 3 3 2 3 2 2 4 5 4 1 1 2 2 2 3 2 3 2 2 2 3 3 3 3 4 1 2 3 2 3 2 4 4
     Levels: 1 < 2 < 3 < 4 < 5
     > ## If instead we generate the formula in the Global environment where
     > ## the variables are not found, we cannot evaluate the model:
     > f2 <- as.formula(rating ~ temp + contact + (1|judge))
     > (try(fm2 <- clmm(f2), silent=TRUE))
     [1] "Error in eval(predvars, data, env) : object 'rating' not found\n"
     attr(,"class")
     [1] "try-error"
     attr(,"condition")
     <simpleError in eval(predvars, data, env): object 'rating' not found>
     > environment(f2) <- environment(f1)
     > fm2 <- clmm(f2)
     >
     > #################################
     > ## Use of formula-objects
     > f <- formula(rating ~ temp + contact + (1|judge))
     > m2 <- clmm(f, data = wine)
     > summary(m2)
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
     :
     --- package (from environment) ---
     ordinal
     --- call from context ---
     summary.clmm(m2)
     --- call from argument ---
     if (class(vc) == "try-error") {
     warning("Variance-covariance matrix of the parameters is not defined")
     coef[, 2:4] <- NaN
     if (correlation)
     warning("Correlation matrix is unavailable")
     object$condHess <- NaN
     } else {
     coef[, 2] <- sd <- sqrt(diag(vc)[1:nfepar])
     object$condHess <- if (any(is.na(object$Hessian)))
     Inf
     else with(eigen(object$Hessian, only.values = TRUE), abs(max(values)/min(values)))
     coef[, 3] <- coef[, 1]/coef[, 2]
     coef[, 4] <- 2 * pnorm(abs(coef[, 3]), lower.tail = FALSE)
     if (correlation)
     object$correlation <- cov2cor(vc)
     }
     --- R stacktrace ---
     where 1: summary.clmm(m2)
     where 2: summary(m2)
    
     --- value of length: 2 type: logical ---
     [1] FALSE FALSE
     --- function from context ---
     function (object, correlation = FALSE, ...)
     {
     if (is.null(object$Hessian))
     stop("Model needs to be fitted with Hess = TRUE")
     nfepar <- object$dims$nfepar
     coef <- matrix(0, nfepar, 4, dimnames = list(names(object$coefficients[1:nfepar]),
     c("Estimate", "Std. Error", "z value", "Pr(>|z|)")))
     coef[, 1] <- object$coefficients[1:nfepar]
     vc <- try(vcov(object), silent = TRUE)
     if (class(vc) == "try-error") {
     warning("Variance-covariance matrix of the parameters is not defined")
     coef[, 2:4] <- NaN
     if (correlation)
     warning("Correlation matrix is unavailable")
     object$condHess <- NaN
     }
     else {
     coef[, 2] <- sd <- sqrt(diag(vc)[1:nfepar])
     object$condHess <- if (any(is.na(object$Hessian)))
     Inf
     else with(eigen(object$Hessian, only.values = TRUE),
     abs(max(values)/min(values)))
     coef[, 3] <- coef[, 1]/coef[, 2]
     coef[, 4] <- 2 * pnorm(abs(coef[, 3]), lower.tail = FALSE)
     if (correlation)
     object$correlation <- cov2cor(vc)
     }
     object$info$cond.H <- formatC(object$condHess, digits = 1,
     format = "e")
     object$coefficients <- coef
     class(object) <- "summary.clmm"
     return(object)
     }
     <bytecode: 0xc2e39c0>
     <environment: namespace:ordinal>
     --- function search by body ---
     Function summary.clmm in namespace ordinal has this body.
     ----------- END OF FAILURE REPORT --------------
     Error in if (class(vc) == "try-error") { : the condition has length > 1
     Calls: summary -> summary.clmm
     Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 2019.4-25
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building 'clm_article.Rnw' using Sweave
    Warning: (1) Hessian is numerically singular: parameters are not uniquely determined
    In addition: Absolute convergence criterion was met, but relative criterion was not met
    Warning: (1) Hessian is numerically singular: parameters are not uniquely determined
    In addition: Absolute convergence criterion was met, but relative criterion was not met
    Warning: (1) Hessian is numerically singular: parameters are not uniquely determined
    In addition: Absolute convergence criterion was met, but relative criterion was not met
    Warning: (-2) Model failed to converge: degenerate Hessian with 1 negative eigenvalues
    In addition: maximum number of consecutive Newton modifications reached
    --- finished re-building 'clm_article.Rnw'
    
    --- re-building 'clmm2_tutorial.Rnw' using Sweave
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
    :
     --- package (from environment) ---
    ordinal
     --- call from context ---
    summary.clmm2(fm2)
     --- call from argument ---
    if (class(vc) == "try-error") {
     warning("Variance-covariance matrix of the parameters is not defined")
     coef[, 2:4] <- NaN
     if (correlation)
     warning("Correlation matrix is unavailable")
     object$condHess <- NaN
    } else {
     sd <- sqrt(diag(vc))
     coef[, 2] <- sd[seq_len(edf - estimStDev)]
     object$condHess <- with(eigen(object$Hessian, only.values = TRUE),
     abs(max(values)/min(values)))
     coef[, 3] <- coef[, 1]/coef[, 2]
     coef[, 4] <- 2 * pnorm(abs(coef[, 3]), lower.tail = FALSE)
     if (correlation)
     object$correlation <- (vc/sd)/rep(sd, rep(object$edf,
     object$edf))
    }
     --- R stacktrace ---
    where 1: summary.clmm2(fm2)
    where 2: summary(fm2)
    where 3: eval(expr, .GlobalEnv)
    where 4: eval(expr, .GlobalEnv)
    where 5: withVisible(eval(expr, .GlobalEnv))
    where 6: doTryCatch(return(expr), name, parentenv, handler)
    where 7: tryCatchOne(expr, names, parentenv, handlers[[1L]])
    where 8: tryCatchList(expr, classes, parentenv, handlers)
    where 9: tryCatch(expr, error = function(e) {
     call <- conditionCall(e)
     if (!is.null(call)) {
     if (identical(call[[1L]], quote(doTryCatch)))
     call <- sys.call(-4L)
     dcall <- deparse(call)[1L]
     prefix <- paste("Error in", dcall, ": ")
     LONG <- 75L
     sm <- strsplit(conditionMessage(e), "\n")[[1L]]
     w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w")
     if (is.na(w))
     w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L],
     type = "b")
     if (w > LONG)
     prefix <- paste0(prefix, "\n ")
     }
     else prefix <- "Error : "
     msg <- paste0(prefix, conditionMessage(e), "\n")
     .Internal(seterrmessage(msg[1L]))
     if (!silent && isTRUE(getOption("show.error.messages"))) {
     cat(msg, file = outFile)
     .Internal(printDeferredWarnings())
     }
     invisible(structure(msg, class = "try-error", condition = e))
    })
    where 10: try(withVisible(eval(expr, .GlobalEnv)), silent = TRUE)
    where 11: evalFunc(ce, options)
    where 12: tryCatchList(expr, classes, parentenv, handlers)
    where 13: tryCatch(evalFunc(ce, options), finally = {
     cat("\n")
     sink()
    })
    where 14: driver$runcode(drobj, chunk, chunkopts)
    where 15: utils::Sweave(...)
    where 16: engine$weave(file, quiet = quiet, encoding = enc)
    where 17: doTryCatch(return(expr), name, parentenv, handler)
    where 18: tryCatchOne(expr, names, parentenv, handlers[[1L]])
    where 19: tryCatchList(expr, classes, parentenv, handlers)
    where 20: 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 21: tools:::.buildOneVignette("clmm2_tutorial.Rnw", "/home/hornik/tmp/R.check/r-devel-clang/Work/PKGS/ordinal.Rcheck/vign_test/ordinal",
     TRUE, FALSE, "clmm2_tutorial", "UTF-8", "/tmp/RtmpY0lvvH/file143b1a1e5eb2.rds")
    
     --- value of length: 2 type: logical ---
    [1] FALSE FALSE
     --- function from context ---
    function (object, digits = max(3, .Options$digits - 3), correlation = FALSE,
     ...)
    {
     estimStDev <- !("sdFixed" %in% names(as.list(object$call)))
     edf <- object$edf
     coef <- with(object, matrix(0, edf - estimStDev, 4, dimnames = list(names(coefficients[seq_len(edf -
     estimStDev)]), c("Estimate", "Std. Error", "z value",
     "Pr(>|z|)"))))
     coef[, 1] <- object$coefficients[seq_len(edf - estimStDev)]
     if (is.null(object$Hessian)) {
     stop("Model needs to be fitted with Hess = TRUE")
     }
     vc <- try(vcov(object), silent = TRUE)
     if (class(vc) == "try-error") {
     warning("Variance-covariance matrix of the parameters is not defined")
     coef[, 2:4] <- NaN
     if (correlation)
     warning("Correlation matrix is unavailable")
     object$condHess <- NaN
     }
     else {
     sd <- sqrt(diag(vc))
     coef[, 2] <- sd[seq_len(edf - estimStDev)]
     object$condHess <- with(eigen(object$Hessian, only.values = TRUE),
     abs(max(values)/min(values)))
     coef[, 3] <- coef[, 1]/coef[, 2]
     coef[, 4] <- 2 * pnorm(abs(coef[, 3]), lower.tail = FALSE)
     if (correlation)
     object$correlation <- (vc/sd)/rep(sd, rep(object$edf,
     object$edf))
     }
     object$coefficients <- coef
     object$digits <- digits
     varMat <- matrix(c(object$stDev^2, object$stDev), nrow = length(object$stDev),
     ncol = 2)
     rownames(varMat) <- names(object$stDev)
     colnames(varMat) <- c("Var", "Std.Dev")
     object$varMat <- varMat
     class(object) <- "summary.clmm2"
     object
    }
    <bytecode: 0xcd97d08>
    <environment: namespace:ordinal>
     --- function search by body ---
    Function summary.clmm2 in namespace ordinal has this body.
     ----------- END OF FAILURE REPORT --------------
    
    Error: processing vignette 'clmm2_tutorial.Rnw' failed with diagnostics:
     chunk 5
    Error in if (class(vc) == "try-error") { : the condition has length > 1
    
    --- failed re-building 'clmm2_tutorial.Rnw'
    
    SUMMARY: processing the following file failed:
     'clmm2_tutorial.Rnw'
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-devel-linux-x86_64-debian-clang