* using log directory ‘/home/hornik/tmp/R.check/r-devel-clang/Work/PKGS/clustrd.Rcheck’ * using R Under development (unstable) (2024-04-27 r86487) * using platform: x86_64-pc-linux-gnu * R was compiled by Debian clang version 18.1.4 (1) Debian flang-new version 18.1.4 (1) * running under: Debian GNU/Linux trixie/sid * using session charset: UTF-8 * checking for file ‘clustrd/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘clustrd’ version ‘1.4.0’ * 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 executable files ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking serialization versions ... OK * checking whether package ‘clustrd’ can be installed ... OK See 'https://www.r-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-clang/clustrd-00install.html' for details. * checking package directory ... OK * checking for future file timestamps ... 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 ... [6s/7s] OK * checking whether the package can be loaded with stated dependencies ... [5s/6s] OK * checking whether the package can be unloaded cleanly ... [5s/6s] OK * checking whether the namespace can be loaded with stated dependencies ... [5s/5s] OK * checking whether the namespace can be unloaded cleanly ... [6s/6s] OK * checking loading without being on the library search path ... [6s/6s] 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 ... [51s/61s] OK * checking Rd files ... [1s/1s] NOTE checkRd: (-1) global_bootclus.Rd:38: Lost braces; missing escapes or markup? 38 | \emph{Step 1. Resampling:} Draw bootstrap samples S_i and T_i of size \emph{n} from the data and use the original data, X, as evaluation set E_i = X. Apply the clustering method of choice to S_i and T_i and obtain C^{S_i} and C^{T_i}. | ^ checkRd: (-1) global_bootclus.Rd:38: Lost braces; missing escapes or markup? 38 | \emph{Step 1. Resampling:} Draw bootstrap samples S_i and T_i of size \emph{n} from the data and use the original data, X, as evaluation set E_i = X. Apply the clustering method of choice to S_i and T_i and obtain C^{S_i} and C^{T_i}. | ^ checkRd: (-1) global_bootclus.Rd:40: Lost braces; missing escapes or markup? 40 | \emph{Step 2. Mapping:} Assign each observation x_i to the closest centers of C^{S_i} and C^{T_i} using Euclidean distance, resulting in partitions C^{XS_i} and C^{XT_i}, where C^{XS_i} is the partition of the original data, X, predicted from clustering bootstrap sample S_i (same for T_i and C^{XT_i}). | ^ checkRd: (-1) global_bootclus.Rd:40: Lost braces; missing escapes or markup? 40 | \emph{Step 2. Mapping:} Assign each observation x_i to the closest centers of C^{S_i} and C^{T_i} using Euclidean distance, resulting in partitions C^{XS_i} and C^{XT_i}, where C^{XS_i} is the partition of the original data, X, predicted from clustering bootstrap sample S_i (same for T_i and C^{XT_i}). | ^ checkRd: (-1) global_bootclus.Rd:40: Lost braces; missing escapes or markup? 40 | \emph{Step 2. Mapping:} Assign each observation x_i to the closest centers of C^{S_i} and C^{T_i} using Euclidean distance, resulting in partitions C^{XS_i} and C^{XT_i}, where C^{XS_i} is the partition of the original data, X, predicted from clustering bootstrap sample S_i (same for T_i and C^{XT_i}). | ^ checkRd: (-1) global_bootclus.Rd:40: Lost braces; missing escapes or markup? 40 | \emph{Step 2. Mapping:} Assign each observation x_i to the closest centers of C^{S_i} and C^{T_i} using Euclidean distance, resulting in partitions C^{XS_i} and C^{XT_i}, where C^{XS_i} is the partition of the original data, X, predicted from clustering bootstrap sample S_i (same for T_i and C^{XT_i}). | ^ checkRd: (-1) global_bootclus.Rd:40: Lost braces; missing escapes or markup? 40 | \emph{Step 2. Mapping:} Assign each observation x_i to the closest centers of C^{S_i} and C^{T_i} using Euclidean distance, resulting in partitions C^{XS_i} and C^{XT_i}, where C^{XS_i} is the partition of the original data, X, predicted from clustering bootstrap sample S_i (same for T_i and C^{XT_i}). | ^ checkRd: (-1) global_bootclus.Rd:40: Lost braces; missing escapes or markup? 40 | \emph{Step 2. Mapping:} Assign each observation x_i to the closest centers of C^{S_i} and C^{T_i} using Euclidean distance, resulting in partitions C^{XS_i} and C^{XT_i}, where C^{XS_i} is the partition of the original data, X, predicted from clustering bootstrap sample S_i (same for T_i and C^{XT_i}). | ^ checkRd: (-1) global_bootclus.Rd:53: Lost braces; missing escapes or markup? 53 | \item{clust1}{Partitions, C^{XS_i} of the original data, X, predicted from clustering bootstrap sample S_i (see Details)} | ^ checkRd: (-1) global_bootclus.Rd:54: Lost braces; missing escapes or markup? 54 | \item{clust2}{Partitions, C^{XT_i} of the original data, X, predicted from clustering bootstrap sample T_i (see Details)} | ^ checkRd: (-1) local_bootclus.Rd:37: Lost braces; missing escapes or markup? 37 | \emph{Step 1. Resampling:} Draw bootstrap samples S_i and T_i of size n from the data and use the original data as evaluation set E_i = X. Apply a joint dimension reduction and clustering method to S_i and T_i and obtain C^{S_i} and C^{T_i}. | ^ checkRd: (-1) local_bootclus.Rd:37: Lost braces; missing escapes or markup? 37 | \emph{Step 1. Resampling:} Draw bootstrap samples S_i and T_i of size n from the data and use the original data as evaluation set E_i = X. Apply a joint dimension reduction and clustering method to S_i and T_i and obtain C^{S_i} and C^{T_i}. | ^ checkRd: (-1) local_bootclus.Rd:39: Lost braces; missing escapes or markup? 39 | \emph{Step 2. Mapping}: Assign each observation x_i to the closest centers of C^{S_i} and C^{T_i} using Euclidean distance, resulting in partitions C^{XS_i} and C^{XT_i}. | ^ checkRd: (-1) local_bootclus.Rd:39: Lost braces; missing escapes or markup? 39 | \emph{Step 2. Mapping}: Assign each observation x_i to the closest centers of C^{S_i} and C^{T_i} using Euclidean distance, resulting in partitions C^{XS_i} and C^{XT_i}. | ^ checkRd: (-1) local_bootclus.Rd:39: Lost braces; missing escapes or markup? 39 | \emph{Step 2. Mapping}: Assign each observation x_i to the closest centers of C^{S_i} and C^{T_i} using Euclidean distance, resulting in partitions C^{XS_i} and C^{XT_i}. | ^ checkRd: (-1) local_bootclus.Rd:39: Lost braces; missing escapes or markup? 39 | \emph{Step 2. Mapping}: Assign each observation x_i to the closest centers of C^{S_i} and C^{T_i} using Euclidean distance, resulting in partitions C^{XS_i} and C^{XT_i}. | ^ checkRd: (-1) local_bootclus.Rd:41: Lost braces; missing escapes or markup? 41 | \emph{Step 3. Evaluation}: Obtain the maximum Jaccard agreement between each original cluster C_k and each one of the two bootstrap clusters, C_^k'{XS_i} and C_^k'{XT_i} as measure of agreement and stability, and take the average of each pair. | ^ checkRd: (-1) local_bootclus.Rd:41: Lost braces; missing escapes or markup? 41 | \emph{Step 3. Evaluation}: Obtain the maximum Jaccard agreement between each original cluster C_k and each one of the two bootstrap clusters, C_^k'{XS_i} and C_^k'{XT_i} as measure of agreement and stability, and take the average of each pair. | ^ checkRd: (-1) local_bootclus.Rd:54: Lost braces; missing escapes or markup? 54 | \item{clust1}{Partitions, C^{XS_i} of the original data, X, predicted from clustering bootstrap sample S_i (see Details)} | ^ checkRd: (-1) local_bootclus.Rd:55: Lost braces; missing escapes or markup? 55 | \item{clust2}{Partitions, C^{XT_i} of the original data, X, predicted from clustering bootstrap sample T_i (see Details)} | ^ * checking Rd metadata ... OK * checking Rd line widths ... 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 contents of ‘data’ directory ... OK * checking data for non-ASCII characters ... [0s/1s] OK * checking data for ASCII and uncompressed saves ... OK * checking examples ... [41s/48s] OK Examples with CPU (user + system) or elapsed time > 5s user system elapsed global_bootclus 6.776 0.007 7.583 cluspca 5.378 0.072 5.866 plot.cluspca 4.758 0.015 6.431 plot.clusmca 4.486 0.012 5.109 * checking PDF version of manual ... [6s/8s] OK * checking HTML version of manual ... [1s/2s] OK * checking for non-standard things in the check directory ... OK * DONE Status: 1 NOTE