Statistical Modelling for Plant Size Distributions
Trees height and diameter at breast height
Computing probability density function of the gamma shape mixture mode...
Computing the probability density function of Johnson's SB (JSB) distr...
Computing probability density function of the well-known mixture model...
Estimating parameters of the Johnson's SB (JSB) distribution using the...
Estimating parameters of the Weibull distribution using the Bayesian a...
Estimatinng the parameters of the nonlinear curve fitted to the height...
Estimating parameters of the three-parameter Birnbaum-saunders (BS), g...
Estimating parameters of the three-parameter Birnbaum-saunders (BS), g...
Estimating parameters of the gamma shape mixture model
Estimating parameters of the Johnson's SB (JSB) distribution using fou...
Estimating parameters of the well-known mixture models
Estimating parameters of the well-known mixture models fitted to the g...
Estimating parameters of the Weibull distribution through classical me...
Mixed norther hardwood
Computing cumulative distribution function of the gamma shape mixture ...
Computing the cumulative distribution function of Johnson's SB (JSB) d...
Computing cumulative distribution function of the well-known mixture m...
Simulating realizations from the gamma shape mixture model
Simulating realizations from the Johnson's SB (JSB) distribution
Generating random realizations from the well-known mixture models
Robust multiple linear regression modelling when error term follows a ...
Southern loblolly pine plantation
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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.