Package: ForestFit
Type: Package
Title: Statistical Modelling for Plant Size Distributions
Author: Mahdi Teimouri
Maintainer: Mahdi Teimouri <teimouri@aut.ac.ir>
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)
<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, and 9 ) Robust multiple linear regression analysis when error
term follows skewed t distribution.
Encoding: UTF-8
License: GPL (>= 2)
Depends: R(>= 3.3.0)
Imports: ars, pracma
Repository: CRAN
Version: 0.6.1
Date: 2020-07-08
NeedsCompilation: no
Packaged: 2020-07-08 10:55:01 UTC; NikPardaz
Date/Publication: 2020-07-08 11:10:02 UTC

Package: ForestFit
Type: Package
Title: Statistical Modelling for Plant Size Distributions
Author: Mahdi Teimouri
Maintainer: Mahdi Teimouri <teimouri@aut.ac.ir>
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)
<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, and 10 ) Estimating
parameters of a given distribution fitted to grouped data using method of maximum
likelihood.
Encoding: UTF-8
License: GPL (>= 2)
Depends: R(>= 3.3.0)
Imports: ars, pracma
Repository: CRAN
Version: 0.7.1
Date: 2021-02-06
NeedsCompilation: no
Packaged: 2021-02-06 13:44:12 UTC; NikPardaz
Date/Publication: 2021-02-06 14:00:02 UTC