CRAN Package Check Results for Package ForestFit

Last updated on 2024-07-22 20:55:42 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 2.2.3 12.60 76.59 89.19 NOTE
r-devel-linux-x86_64-debian-gcc 2.2.3 11.25 54.43 65.68 NOTE
r-devel-linux-x86_64-fedora-clang 2.2.3 109.25 NOTE
r-devel-linux-x86_64-fedora-gcc 2.2.3 101.69 NOTE
r-devel-windows-x86_64 2.2.3 12.00 70.00 82.00 NOTE
r-patched-linux-x86_64 2.2.3 11.89 69.78 81.67 NOTE
r-release-linux-x86_64 2.2.3 14.28 71.69 85.97 NOTE
r-release-macos-arm64 2.2.3 28.00 NOTE
r-release-macos-x86_64 2.2.3 46.00 NOTE
r-release-windows-x86_64 2.2.3 11.00 71.00 82.00 NOTE
r-oldrel-macos-arm64 2.2.3 31.00 OK
r-oldrel-macos-x86_64 2.2.3 47.00 OK
r-oldrel-windows-x86_64 2.2.3 10.00 75.00 85.00 OK

Check Details

Version: 2.2.3
Check: Rd files
Result: NOTE checkRd: (-1) fitJSB.Rd:21: Lost braces 21 | \item A sequence of four goodness-of-fit measures consist of Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics. | ^ checkRd: (-1) fitWeibull.Rd:46: Lost braces 46 | \item A sequence of goodness-of-fit measures consist of Akaike Information Criterion (\code{AIC}), Consistent Akaike Information Criterion (\code{CAIC}), Bayesian Information Criterion (\code{BIC}), Hannan-Quinn information criterion (\code{HQIC}), Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics.} | ^ checkRd: (-1) fitbayesJSB.Rd:19: Lost braces 19 | \item A sequence of four goodness-of-fit measures consist of Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics. | ^ checkRd: (-1) fitbayesWeibull.Rd:15: Lost braces 15 | \item A sequence of four goodness-of-fit measures consist of Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics. | ^ checkRd: (-1) fitgrouped1.Rd:32: Lost braces 32 | Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics. | ^ checkRd: (-1) fitgrouped2.Rd:27: Lost braces 27 | \item A sequence of goodness-of-fit measures consist of Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), and Kolmogorov-Smirnov (\code{KS}) statistics. | ^ checkRd: (-1) fitgsm.Rd:17: Lost braces 17 | \item A sequence of goodness-of-fit measures consist of Akaike Information Criterion (\code{AIC}), Consistent Akaike Information Criterion (\code{CAIC}), Bayesian Information Criterion (\code{BIC}), Hannan-Quinn information criterion (\code{HQIC}), Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics.} | ^ checkRd: (-1) fitmixture.Rd:19: Lost braces 19 | \item The second part involves a sequence of goodness-of-fit measures consist of Akaike Information Criterion (\code{AIC}), Consistent Akaike Information Criterion (\code{CAIC}), Bayesian Information Criterion (\code{BIC}), Hannan-Quinn information criterion (\code{HQIC}), Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics. | ^ checkRd: (-1) fitmixturegrouped.Rd:28: Lost braces 28 | \item A sequence of goodness-of-fit measures consist of Akaike Information Criterion (\code{AIC}), Consistent Akaike Information Criterion (\code{CAIC}), Bayesian Information Criterion (\code{BIC}), Hannan-Quinn information criterion (\code{HQIC}), Anderson-Darling (\code{AD}), Cram\'{e}er-von Misses (\code{CVM}), Kolmogorov-Smirnov (\code{KS}), and log-likelihood (\code{log-likelihood}) statistics.} | ^ checkRd: (-1) rmixture.Rd:6: Lost braces 6 | where \eqn{K} is the number of components, \eqn{\theta_j}, for \eqn{j=1,\dots,K} is parameter space of the \eqn{j}-th component, i.e. \eqn{\theta_j=(\alpha_j,\beta_j)^{T}}, and \eqn{\Theta} is the whole parameter vector \eqn{\Theta=(\theta_1,\dots,\theta_K)^{T}}. Parameters \eqn{\alpha} and \eqn{\beta} are the shape and scale parameters or both are the shape parameters. In the latter case, parameters \eqn{\alpha} and \eqn{\beta} are called the first and second shape parameters, respectively. We note that the constants \eqn{\omega_j}s sum to one, i.e., \eqn{\sum_{j=1}^{K}\omega_j=1}. The families considered for the cdf \eqn{f} include Birnbaum-Saunders, Burr type XII, Chen, F, Fr{\'e}chet, Gamma, Gompertz, Log-normal, Log-logistic, Lomax, skew-normal, and Weibull.} | ^ 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