- using R Under development (unstable) (2024-05-10 r86529)
- using platform: x86_64-pc-linux-gnu
- R was compiled by clang version 18.1.5 flang-new version 18.1.5
- running under: Fedora Linux 36 (Workstation Edition)
- using session charset: UTF-8
- using option ‘--no-stop-on-test-error’
- checking for file ‘clustrd/DESCRIPTION’ ... OK
- checking extension type ... Package
- this is package ‘clustrd’ version ‘1.4.0’
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- checking whether package ‘clustrd’ can be installed ... [36s/40s] OK See the install log for details.
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- checking Rd files ... 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)} | ^
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- checking contents of ‘data’ directory ... OK
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- checking examples ... [50s/72s] OK
- checking PDF version of manual ... [8s/11s] OK
- checking HTML version of manual ... OK
- checking for non-standard things in the check directory ... OK
- checking for detritus in the temp directory ... OK
- DONE

Status: 1 NOTE