CRAN Package Check Results for Package ForestFit

Last updated on 2024-11-21 19:52:37 CET.

Flavor	Version	Tinstall	Tcheck	Ttotal	Status	Flags
r-devel-linux-x86_64-debian-clang	2.2.3	13.17	55.82	68.99	NOTE
r-devel-linux-x86_64-debian-gcc	2.2.3	6.85	36.63	43.48	NOTE
r-devel-linux-x86_64-fedora-clang	2.2.3			111.90	NOTE
r-devel-linux-x86_64-fedora-gcc	2.2.3			103.10	NOTE
r-devel-windows-x86_64	2.2.3	11.00	72.00	83.00	NOTE
r-patched-linux-x86_64	2.2.3	11.89	53.14	65.03	NOTE
r-release-linux-x86_64	2.2.3	11.58	52.16	63.74	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	9.00	94.00	103.00	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	74.00	84.00	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