Package: MLEce 2.1.0

MLEce: Asymptotic Efficient Closed-Form Estimators for Multivariate Distributions

Asymptotic efficient closed-form estimators (MLEces) are provided in this package for three multivariate distributions(gamma, Weibull and Dirichlet) whose maximum likelihood estimators (MLEs) are not in closed forms. Closed-form estimators are strong consistent, and have the similar asymptotic normal distribution like MLEs. But the calculation of MLEces are much faster than the corresponding MLEs. Further details and explanations of MLEces can be found in. Jang, et al. (2023) <doi:10.1111/stan.12299>. Kim, et al. (2023) <doi:10.1080/03610926.2023.2179880>.

Authors:Jun Zhao [aut, cre, com], Yu-Kwang Kim [aut], Yu-Hyeong Jang [aut], Jae Ho Chang [aut], Sang Kyu Lee [aut], Hyoung-Moon Kim [aut, ths]

MLEce_2.1.0.tar.gz
MLEce_2.1.0.zip(r-4.7-any)MLEce_2.1.0.zip(r-4.6-any)MLEce_2.1.0.zip(r-4.5-any)
MLEce_2.1.0.tgz(r-4.6-any)MLEce_2.1.0.tgz(r-4.5-any)
MLEce_2.1.0.tar.gz(r-4.7-any)MLEce_2.1.0.tar.gz(r-4.6-any)
MLEce_2.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
MLEce/json (API)

# Install 'MLEce' in R:
install.packages('MLEce', repos = c('https://ijun2018.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ijun2018/mlece/issues

Datasets:
  • flood - The flood events data of the Madawaska basin.
  • fossil_pollen - The counts data of the frequency of occurrence of different kinds of fossil pollen grains.

On CRAN:

Conda:

2.70 score 235 downloads 6 exports 33 dependencies

Last updated from:d20a9ef7d8. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK140
source / vignettesOK228
linux-release-x86_64OK177
macos-release-arm64OK142
macos-oldrel-arm64OK213
windows-develOK95
windows-releaseOK98
windows-oldrelOK100
wasm-releaseOK100

Exports:benchMLEceconfCIgofMLEcerBiGamrBiWei

Dependencies:admiscCDMclicpp11farverggplot2gluegtableisobandlabelingLaplacesDemonlatticelifecycleMatrixmvtnormnleqslvpbapplypbvplyrpolycorR6RColorBrewerRcppRcppArmadilloreshaperlangS7scalessirtTAMvctrsviridisLitewithr