Last updated on 2025-05-03 12:54:37 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.4.0 | 21.20 | 163.80 | 185.00 | NOTE | |
| r-devel-linux-x86_64-debian-gcc | 1.4.0 | 12.59 | 111.50 | 124.09 | NOTE | |
| r-devel-linux-x86_64-fedora-clang | 1.4.0 | 286.83 | NOTE | |||
| r-devel-linux-x86_64-fedora-gcc | 1.4.0 | 276.49 | NOTE | |||
| r-devel-windows-x86_64 | 1.4.0 | 20.00 | 147.00 | 167.00 | NOTE | |
| r-patched-linux-x86_64 | 1.4.0 | 21.70 | 154.08 | 175.78 | NOTE | |
| r-release-linux-x86_64 | NOTE | |||||
| r-release-macos-arm64 | 1.4.0 | 67.00 | NOTE | |||
| r-release-macos-x86_64 | 1.4.0 | 157.00 | NOTE | |||
| r-release-windows-x86_64 | 1.4.0 | 20.00 | 147.00 | 167.00 | NOTE | |
| r-oldrel-macos-arm64 | 1.4.0 | 68.00 | NOTE | |||
| r-oldrel-macos-x86_64 | 1.4.0 | 106.00 | NOTE | |||
| r-oldrel-windows-x86_64 | 1.4.0 | 27.00 | 207.00 | 234.00 | NOTE |
Version: 1.4.0
Check: CRAN incoming feasibility
Result: NOTE
Maintainer: ‘Angelos Markos <amarkos@gmail.com>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: c(person(given = "Angelos",
family = "Markos",
role = c("aut", "cre"),
email = "amarkos@gmail.com"),
person(given = c("Alfonso", "Iodice"),
family = "D'Enza",
role = "aut"),
person(given = "Michel",
family = "van de Velden",
role = "aut"))
as necessary.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 1.4.0
Check: Rd files
Result: 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)}
| ^
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64