Density, distribution, quantile, random number generation and parameter estimation functions for the Laplace distribution with location parameter μ and scale parameter b. Parameter estimation can for the Laplace distribution can be carried out numerically or analytically but may only be based on an unweighted i.i.d. sample.
Beta_ab
(Package: ExtDist) :
The four-parameter beta distribution.
Density, distribution, quantile, random number generation, and parameter estimation functions for the 4-parameter beta distribution. Parameter estimation can be based on a weighted or unweighted i.i.d sample and can be performed numerically.
Density, distribution, quantile, random number generation, and parameter estimation functions for the Weibull distribution with parameters shape and scale. Parameter estimation can be based on a weighted or unweighted i.i.d sample and can be carried out analytically or numerically.
The package provides a consistent, unified and extensible framework for parameter estimation of probability distributions; it extends parameter estimation procedures to allow for weighted samples; moreover, it extends the gallery of available distributions.
Density, distribution, quantile, random number generation and parameter estimation functions for the symmetric truncated normal distribution with parameters, sigma, a and b which represent the lower and upper truncation points respectively. Parameter estimation can be based on a weighted or unweighted i.i.d sample and can be carried out numerically.
SRTB_ab
(Package: ExtDist) :
The symmetric-reflected truncated beta (SRTB) distribution.
Density, distribution, quantile, random number generation and parameter estimation functions for the SRTB distribution. Parameter estimation can be based on a weighted or unweighted i.i.d. sample and can be carried out numerically.
Density, distribution, and quantile, random number generation, and parameter estimation functions for the logistic distribution with parameters location and scale. Parameter estimation can be based on a weighted or unweighted i.i.d. sample and can be carried out numerically.
Density, distribution, quantile, random number generation, and parameter estimation functions for the Johnson SB (bounded support) distribution. Parameter estimation can be based on a weighted or unweighted i.i.d. sample and can be performed numerically.