* using log directory 'd:/Rcompile/CRANpkg/local/4.6/lolR.Rcheck' * using R version 4.6.1 (2026-06-24 ucrt) * using platform: x86_64-w64-mingw32 * R was compiled by gcc.exe (GCC) 14.3.0 GNU Fortran (GCC) 14.3.0 * running under: Windows Server 2022 x64 (build 20348) * using session charset: UTF-8 * current time: 2026-08-12 12:41:29 UTC * checking for file 'lolR/DESCRIPTION' ... OK * checking extension type ... Package * this is package 'lolR' version '2.1' * package encoding: UTF-8 * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking whether package 'lolR' can be installed ... OK * checking installed package size ... OK * checking package directory ... OK * checking 'build' directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking code files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... [2s] OK * checking whether the package can be loaded with stated dependencies ... [2s] OK * checking whether the package can be unloaded cleanly ... [2s] OK * checking whether the namespace can be loaded with stated dependencies ... [2s] OK * checking whether the namespace can be unloaded cleanly ... [2s] OK * checking loading without being on the library search path ... [2s] OK * checking use of S3 registration ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... [7s] OK * checking Rd files ... [1s] NOTE checkRd: (-1) lol.project.lrlda.Rd:18: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.project.lrlda.Rd:19: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.project.lrlda.Rd:20: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.project.lrlda.Rd:21: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.project.lrlda.Rd:22: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.project.pca.Rd:16: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.project.pca.Rd:17: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.project.pca.Rd:18: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.project.pca.Rd:19: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.project.pca.Rd:20: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.sims.fat_tails.Rd:25: Lost braces; missing escapes or markup? 25 | \item{f}{the fatness scaling of the tail. S2 = f*S1, where S1_{ij} = rho if i != j, and 1 if i == j. Defaults to \code{15}.} | ^ checkRd: (-1) lol.sims.mean_diff.Rd:36: Lost braces; missing escapes or markup? 36 | \item{s}{the scaling parameter of the covariance matrix. S_{ij} = scaling*1 if i == j, or scaling*offdiag if i != j. Defaults to \code{1}.} | ^ checkRd: (-1) lol.utils.decomp.Rd:21: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.utils.decomp.Rd:22: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.utils.decomp.Rd:23: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.utils.decomp.Rd:24: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.utils.decomp.Rd:25: Lost braces in \itemize; meant \describe ? checkRd: (-1) lol.xval.eval.Rd:31: Lost braces; missing escapes or markup? 31 | \item{alg}{the algorithm to use for embedding. Should be a function that accepts inputs \code{X}, \code{Y}, and has a parameter for \code{alg.dimname} if \code{alg} is supervised, or just \code{X} and \code{alg.dimname} if \code{alg} is unsupervised.This algorithm should return a list containing a matrix that embeds from {d} to {r <= d} dimensions.} | ^ checkRd: (-1) lol.xval.eval.Rd:31: Lost braces; missing escapes or markup? 31 | \item{alg}{the algorithm to use for embedding. Should be a function that accepts inputs \code{X}, \code{Y}, and has a parameter for \code{alg.dimname} if \code{alg} is supervised, or just \code{X} and \code{alg.dimname} if \code{alg} is unsupervised.This algorithm should return a list containing a matrix that embeds from {d} to {r <= d} dimensions.} | ^ checkRd: (-1) lol.xval.eval.Rd:68: Lost braces 68 | \item{if ]code{rank.low == TRUE}, users cross-validation method with \code{ntrain = min((k-1)/k*n, d)} sample training sets, where \code{d} is the number of dimensions in \code{X}. This ensures that the training data is always low-rank, \code{ntrain < d + 1}. Note that the resulting training sets may have \code{ntrain < (k-1)/k*n}, but the resulting testing sets will always be properly rotated \code{ntest = n/k} to ensure no dependencies in fold-wise testing.} | ^ checkRd: (-1) lol.xval.optimal_dimselect.Rd:32: Lost braces; missing escapes or markup? 32 | \item{alg}{the algorithm to use for embedding. Should be a function that accepts inputs \code{X} and \code{Y} and embedding dimension \code{r} if \code{alg} is supervised, or just \code{X} and embedding dimension \code{r} if \code{alg} is unsupervised.This algorithm should return a list containing a matrix that embeds from {d} to {r < d} dimensions.} | ^ checkRd: (-1) lol.xval.optimal_dimselect.Rd:32: Lost braces; missing escapes or markup? 32 | \item{alg}{the algorithm to use for embedding. Should be a function that accepts inputs \code{X} and \code{Y} and embedding dimension \code{r} if \code{alg} is supervised, or just \code{X} and embedding dimension \code{r} if \code{alg} is unsupervised.This algorithm should return a list containing a matrix that embeds from {d} to {r < d} dimensions.} | ^ checkRd: (-1) lol.xval.optimal_dimselect.Rd:75: Lost braces 75 | \item{if ]code{rank.low == TRUE}, users cross-validation method with \code{ntrain = min((k-1)/k*n, d)} sample training sets, where \code{d} is the number of dimensions in \code{X}. This ensures that the training data is always low-rank, \code{ntrain < d + 1}. Note that the resulting training sets may have \code{ntrain < (k-1)/k*n}, but the resulting testing sets will always be properly rotated \code{ntest = n/k} to ensure no dependencies in fold-wise testing.} | ^ checkRd: (-1) predict.nearestCentroid.Rd:12: Lost braces in \itemize; meant \describe ? checkRd: (-1) predict.nearestCentroid.Rd:13: Lost braces in \itemize; meant \describe ? checkRd: (-1) predict.nearestCentroid.Rd:14: Lost braces in \itemize; meant \describe ? checkRd: (-1) predict.randomChance.Rd:12: Lost braces in \itemize; meant \describe ? checkRd: (-1) predict.randomChance.Rd:13: Lost braces in \itemize; meant \describe ? checkRd: (-1) predict.randomGuess.Rd:12: Lost braces in \itemize; meant \describe ? checkRd: (-1) predict.randomGuess.Rd:13: Lost braces in \itemize; meant \describe ? * checking Rd metadata ... OK * checking Rd cross-references ... OK * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking LazyData ... INFO 'LazyData' is specified without a 'data' directory * checking installed files from 'inst/doc' ... OK * checking files in 'vignettes' ... OK * checking examples ... [11s] OK * checking for unstated dependencies in 'tests' ... OK * checking tests ... [12s] OK Running 'testthat.R' [12s] * checking for unstated dependencies in vignettes ... OK * checking package vignettes ... OK * checking re-building of vignette outputs ... [108s] OK * checking PDF version of manual ... [28s] OK * checking HTML version of manual ... [11s] OK * DONE Status: 1 NOTE Check process probably crashed or hung up for 20 minutes ... killed Most likely this happened in the example checks (?), if not, ignore the following last lines of example output: > > ### Name: predict.randomGuess > ### Title: Randomly Guessing Classifier Prediction > ### Aliases: predict.randomGuess > > ### ** Examples > > library(lolR) > data <- lol.sims.rtrunk(n=200, d=30) # 200 examples of 30 dimensions > X <- data$X; Y <- data$Y > model <- lol.classify.randomGuess(X, Y) > Yh <- predict(model, X) > > > > ### *