Package: ForestFit 2.2.3

ForestFit: Statistical Modelling for Plant Size Distributions

Developed for the following tasks. 1 ) Computing the probability density function, cumulative distribution function, random generation, and estimating the parameters of the eleven mixture models. 2 ) Point estimation of the parameters of two - parameter Weibull distribution using twelve methods and three - parameter Weibull distribution using nine methods. 3 ) The Bayesian inference for the three - parameter Weibull distribution. 4 ) Estimating parameters of the three - parameter Birnbaum - Saunders, generalized exponential, and Weibull distributions fitted to grouped data using three methods including approximated maximum likelihood, expectation maximization, and maximum likelihood. 5 ) Estimating the parameters of the gamma, log-normal, and Weibull mixture models fitted to the grouped data through the EM algorithm, 6 ) Estimating parameters of the nonlinear height curve fitted to the height - diameter observation, 7 ) Estimating parameters, computing probability density function, cumulative distribution function, and generating realizations from gamma shape mixture model introduced by Venturini et al. (2008) <doi:10.1214/07-AOAS156> , 8 ) The Bayesian inference, computing probability density function, cumulative distribution function, and generating realizations from four-parameter Johnson SB distribution, 9 ) Robust multiple linear regression analysis when error term follows skewed t distribution, 10 ) Estimating parameters of a given distribution fitted to grouped data using method of maximum likelihood, and 11 ) Estimating parameters of the Johnson SB distribution through the Bayesian, method of moment, conditional maximum likelihood, and two - percentile method.

Authors:Mahdi Teimouri [aut, cre, cph, ctb]

ForestFit_2.2.3.tar.gz
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ForestFit.pdf |ForestFit.html
ForestFit/json (API)

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

Peer review:

Datasets:
  • DBH - Trees height and diameter at breast height
  • HW - Mixed norther hardwood
  • SW - Southern loblolly pine plantation

On CRAN:

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

21 exports 0.00 score 2 dependencies 2 scripts 468 downloads

Last updated 2 years agofrom:a23d6772bb. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 24 2024
R-4.5-winNOTEAug 24 2024
R-4.5-linuxNOTEAug 24 2024
R-4.4-winNOTEAug 24 2024
R-4.4-macNOTEAug 24 2024
R-4.3-winOKAug 24 2024
R-4.3-macOKAug 24 2024

Exports:dgsmdjsbdmixturefitbayesJSBfitbayesWeibullfitcurvefitgrouped1fitgrouped2fitgsmfitJSBfitmixturefitmixturegroupedfitWeibullpgsmpjsbpmixturergsmrjsbrmixtureskewtregwelcome

Dependencies:arspracma

Readme and manuals

Help Manual

Help pageTopics
Trees height and diameter at breast heightDBH
Computing probability density function of the gamma shape mixture modeldgsm
Computing the probability density function of Johnson's SB (JSB) distributiondjsb
Computing probability density function of the well-known mixture modelsdmixture
Estimating parameters of the Johnson's SB (JSB) distribution using the Bayesian approachfitbayesJSB
Estimating parameters of the Weibull distribution using the Bayesian approachfitbayesWeibull
Estimatinng the parameters of the nonlinear curve fitted to the height-diameter(H-D) observationsfitcurve
Estimating parameters of the three-parameter Birnbaum-saunders (BS), generalized exponential (GE), and Weibull distributions fitted to grouped datafitgrouped1
Estimating parameters of the three-parameter Birnbaum-saunders (BS), generalized exponential (GE), and Weibull distributions fitted to grouped datafitgrouped2
Estimating parameters of the gamma shape mixture modelfitgsm
Estimating parameters of the Johnson's SB (JSB) distribution using four methodsfitJSB
Estimating parameters of the well-known mixture modelsfitmixture
Estimating parameters of the well-known mixture models fitted to the grouped datafitmixturegrouped
Estimating parameters of the Weibull distribution through classical methodsfitWeibull
Mixed norther hardwoodHW
Computing cumulative distribution function of the gamma shape mixture modelpgsm
Computing the cumulative distribution function of Johnson's SB (JSB) distributionpjsb
Computing cumulative distribution function of the well-known mixture modelspmixture
Simulating realizations from the gamma shape mixture modelrgsm
Simulating realizations from the Johnson's SB (JSB) distributionrjsb
Generating random realizations from the well-known mixture modelsrmixture
Robust multiple linear regression modelling when error term follows a skew Student's t distributionskewtreg
Southern loblolly pine plantationSW
Starting message when loading ForestFitwelcome