simul.mp: Simulation planning for the parameters of an exponential...

In normalp: Routines for Exponential Power Distribution

Simulation planning for the parameters of an exponential power distribution

Description

This function performs a Monte Carlo simulation to compare least square estimators and Maximum Likelihood estimators for the parameters of an exponential power distribution. For each sample, it calls the function paramp, returning the arithmetic means, the max-likelihood estimates of the location parameter, the standard deviations, the max-likelihood estimates of the scale parameter and the estimates of the shape parameter.

Usage

simul.mp(n, m, mu=0, sigmap=1, p=2)

Arguments

n	Sample size.
m	Number of samples.
mu	Value of the location parameter.
sigmap	Value of the scale parameter.
p	the shape parameter.

Value

This function is useful to compare several kinds of estimators. It returns an object of class "simul.mp", a list containing the following components:

dat	A matrix m\times 5 containing the results of paramp for each sample.
table	A matrix reporting the means and the variances of the values of the five estimators.

Author(s)

Angelo M. Mineo

References

Mineo, A.M. (1995) Stima dei parametri di intensit\'a e di scala di una curva normale di ordine p (p incognito). Annali della Facolt\‘a di Economia dell’Universit\'a di Palermo (Area Statistico-Matematica), pp. 125-159.

Examples

## Simulation plan for 100 samples of size 20, with mu=0, sigmap=1, p=3.
simul.mp(20,100,mu=0,sigmap=1,p=3)

normalp documentation built on May 29, 2024, 10:27 a.m.