CRAN Package Check Results for Package lcpm

Last updated on 2026-09-16 06:49:26 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.1.2 6.95 61.62 68.57 OK
r-devel-linux-x86_64-debian-gcc 0.1.2 5.00 45.75 50.75 OK
r-devel-linux-x86_64-fedora-clang 0.1.2 41.14 OK
r-devel-linux-x86_64-fedora-gcc 0.1.2 44.93 OK
r-devel-windows-x86_64 0.1.1 8.00 90.00 98.00 NOTE
r-patched-linux-x86_64 0.1.1 6.34 57.17 63.51 NOTE
r-release-linux-x86_64 0.1.1 6.36 57.61 63.97 NOTE
r-release-macos-arm64 0.1.1 2.00 17.00 19.00 NOTE
r-release-macos-x86_64 0.1.2 5.00 106.00 111.00 OK
r-release-windows-x86_64 0.1.2 8.00 76.00 84.00 OK
r-oldrel-macos-arm64 0.1.2 2.00 22.00 24.00 OK
r-oldrel-macos-x86_64 0.1.2 5.00 65.00 70.00 OK
r-oldrel-windows-x86_64 0.1.2 12.00 91.00 103.00 OK

Check Details

Version: 0.1.1
Check: Rd files
Result: NOTE checkRd: (-1) lcpm.Rd:52: Lost braces; missing escapes or markup? 52 | \code{lcpm} provides the maximum likelihood estimate for ordinal outcomes (J>2 categories) and a Generalized Linear Model (GLM) with the log link without the assumption of proportionality. That is, lcpm determines the MLE for log[P(y <= j)]= cut_j + X beta_j subject to [cut_{j-1} + X beta_{j-1} <= cut_j + X beta_j] and [cut_j + X beta_j <=0]. This implementation uses \code{\link{constrOptim}} to determine the MLE and so the results account for the restricted parameter space. | ^ checkRd: (-1) lcpm.Rd:52: Lost braces; missing escapes or markup? 52 | \code{lcpm} provides the maximum likelihood estimate for ordinal outcomes (J>2 categories) and a Generalized Linear Model (GLM) with the log link without the assumption of proportionality. That is, lcpm determines the MLE for log[P(y <= j)]= cut_j + X beta_j subject to [cut_{j-1} + X beta_{j-1} <= cut_j + X beta_j] and [cut_j + X beta_j <=0]. This implementation uses \code{\link{constrOptim}} to determine the MLE and so the results account for the restricted parameter space. | ^ checkRd: (-1) ppm.Rd:51: Lost braces; missing escapes or markup? 51 | \code{ppm} provides the maximum likelihood estimate for ordinal outcomes (J>2 categories) and a Generalized Linear Model with the log link with the assumption of proportionality. That is, ppm determines the MLE for log[P(y <= j)]= cut_j + X beta subject to [cut_{j-1} <= cut_j ] and [cut_j + X beta <=0]. This implementation uses \code{\link{constrOptim}} to determine the MLE and so the results should correctly account for the restricted parameter space. A proposed test for proportionality is included in \code{\link{lcpm}}. | ^ Flavors: r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64