simul.lmp: Simulation planning for a linear regression model with errors distributed as an exponential power distribution
Description
This function performs a Monte Carlo simulation to compare least squares estimators and
Maximum Likelihood estimators for a linear regression model with errors distributed as an exponential power
distribution. The regressors are drawn from an Uniform distribution.
Usage
simul.lmp(n, m, q, data, int=0, sigmap=1, p=2, lp=FALSE)
Value
The function simul.lmp returns an object of class "simul.lmp". A component of this object
is a table of means and variances of the \(m\) estimates of the regression coefficients and
of the scale paramenter \(\sigma_p\).
The summary shows this table and the arguments of the simulation plan. The function plot
returns the histograms of the computed estimates.
Arguments
n
Sample size.
m
Number of samples.
q
Number of regressors.
data
A vector of coefficients.
int
Value of the intercept.
sigmap
The scale parameter.
p
The shape parameter.
lp
Logical. If TRUE, it evaluates the coefficients with p known.
Author
Angelo M. Mineo
References
Mineo, A.M. (1995) Stima dei parametri di regressione lineare semplice quando gli errori seguono una
distribuzione normale di ordine p (p incognito). Annali della Facolt\`a di Economia dell'Universit\`a
di Palermo (Area Statistico-Matematica), pp. 161-186.