Learn R Programming

⚠️There's a newer version (2.4.3) of this package.Take me there.

ForestFit (version 0.6.1)

Statistical Modelling for Plant Size Distributions

Description

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) , 8 ) The Bayesian inference, computing probability density function, cumulative distribution function, and generating realizations from four - parameter Johnson SB distribution, and 9 ) Robust multiple linear regression analysis when error term follows skewed t distribution.

Copy Link

Version

Install

install.packages('ForestFit')

Monthly Downloads

392

Version

0.6.1

License

GPL (>= 2)

Maintainer

Mahdi Teimouri

Last Published

July 8th, 2020

Functions in ForestFit (0.6.1)

fitcurve

Estimatinng the parameters of the nonlinear curve fitted to the height-diameter(H-D) observations
HW

Mixed norther hardwood
dmixture

Computing probability density function of the well-known mixture models
dgsm

Computing probability density function of the gamma shape mixture model
djsb

Computing the probability density function of Johnson's SB (JSB) distribution
fitWeibull

Estimating parameters of the Weibull distribution through classical methods
fitbayesWeibull

Estimating parameters of the Weibull distribution using the Bayesian approach
SW

Southern loblolly pine plantation
DBH

Trees height and diameter at breast height
fitbayesJSB

Estimating parameters of the Johnson's SB (JSB) distribution using the Bayesian approach
pgsm

Computing cumulative distribution function of the gamma shape mixture model
fitgsm

Estimating parameters of the gamma shape mixture model
fitgrouped

Estimating parameters of the three-parameter Birnbaum-saunders (BS), generalized exponential (GE), and Weibull distributions fitted to grouped data
pjsb

Computing the cumulative distribution function of Johnson's SB (JSB) distribution
pmixture

Computing cumulative distribution function of the well-known mixture models
rgsm

Simulating realizations from the gamma shape mixture model
welcome

Starting message when loading ForestFit
skewtreg

Robust multiple linear regression modelling when error term follows a skew Student's \(t\) distribution
fitmixture

Estimating parameters of the well-known mixture models
fitmixturegrouped

Estimating parameters of the well-known mixture models fitted to the grouped data
rmixture

Generating random realizations from the well-known mixture models
rjsb

Simulating realizations from the Johnson's SB (JSB) distribution