Package: ExGaussEstim 0.1.2

ExGaussEstim: Quantile Maximization Likelihood Estimation and Bayesian Ex-Gaussian Estimation

Presents two methods to estimate the parameters 'mu', 'sigma', and 'tau' of an ex-Gaussian distribution. Those methods are Quantile Maximization Likelihood Estimation ('QMLE') and Bayesian. The 'QMLE' method allows a choice between three different estimation algorithms for these parameters : 'neldermead' ('NEMD'), 'fminsearch' ('FMIN'), and 'nlminb' ('NLMI'). For more details about the methods you can refer at the following list: Brown, S., & Heathcote, A. (2003) <doi:10.3758/BF03195527>; McCormack, P. D., & Wright, N. M. (1964) <doi:10.1037/h0083285>; Van Zandt, T. (2000) <doi:10.3758/BF03214357>; El Haj, A., Slaoui, Y., Solier, C., & Perret, C. (2021) <doi:10.19139/soic-2310-5070-1251>; Gilks, W. R., Best, N. G., & Tan, K. K. C. (1995) <doi:10.2307/2986138>.

Authors:Yousri SLAOUI [aut], Abir EL HAJ [aut, ctb], Alandra ZAKKOUR [aut], Caroline BORDES [aut, ctb], Cyril PERRET [aut], Jean DUMONCEL [aut, cre]

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ExGaussEstim/json (API)

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

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 scripts 205 downloads 2 exports 11 dependencies

Last updated 1 years agofrom:0b475d02cd. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 21 2024
R-4.5-winNOTENov 21 2024
R-4.5-linuxNOTENov 21 2024
R-4.4-winNOTENov 21 2024
R-4.4-macNOTENov 21 2024
R-4.3-winNOTENov 21 2024
R-4.3-macNOTENov 21 2024

Exports:BayesianExgaussianQMLEEstim

Dependencies:dlmfitdistrplusgamlss.distinvgammalatticeMASSMatrixnloptrpracmarlangsurvival