Developed for the following tasks . I ) Computing the probability density function ,
cumulative distribution function , random generation , and estimating the parameters
of the eleven mixture models . II ) Point estimation of the parameters of two -
parameter Weibull distribution using twelve methods and three - parameter Weibull
distribution using nine methods . III ) The Bayesian estimators of the three -
parameter Weibull distribution . IV ) 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 . V ) Estimating the parameters
of the gamma , log-normal , and Weibull mixture models fitted to the grouped data
through the EM algorithm , VI ) Estimating parameters of the nonlinear height curve
fitted to the height - diameter observation , VII ) 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> , and VIII ) Robust multiple linear regression analysis when
error term follows skewed t distribution .

Developed for the following tasks. I ) Computing the probability density function,
cumulative distribution function, random generation, and estimating the parameters
of the eleven mixture models. II ) Point estimation of the parameters of two -
parameter Weibull distribution using twelve methods and three - parameter Weibull
distribution using nine methods. III ) The Bayesian estimators of the three -
parameter Weibull distribution. IV ) 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. V ) Estimating the parameters
of the gamma, log-normal, and Weibull mixture models fitted to the grouped data
through the EM algorithm, VI ) Estimating parameters of the nonlinear height curve
fitted to the height - diameter observation, VII ) 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> , and VIII ) Robust multiple linear regression analysis when
error term follows skewed t distribution.