est.utpn: Parameter estimation for the utpn model

In tpn: Truncated Positive Normal Model and Extensions

Parameter estimation for the utpn model

Description

Perform the parameter estimation for the unit truncated positive normal (utpn) type 1, 2, 3 or 4, parameterized in terms of the quantile based on maximum likelihood estimation. Estimated errors are computed based on the hessian matrix.

Usage

est.utpn(y, x=NULL, type=1, link="logit", q=0.5)

Arguments

y	the response vector. All the values must be positive.
x	the covariates vector.
type	to distinguish the type of the utpn model: 1 (default), 2, 3 or 4.
link	link function to be used for the covariates: logit (default).
q	quantile of the distribution to be modelled.

Value

A list with the following components

estimate	A matrix with the estimates and standard errors
logLik	log-likelihood function evaluated in the estimated parameters.
AIC	Akaike's criterion.
BIC	Schwartz's criterion.

Note

A warning is presented if the estimated hessian matrix is not invertible.

Author(s)

Gallardo, D.I.

References

Gomez, H.J., Olmos, N.M., Varela, H., Bolfarine, H. (2018). Inference for a truncated positive normal distribution. Applied Mathemetical Journal of Chinese Universities, 33, 163-176.

Examples

set.seed(2021)
y=rutpn(n=100,sigma=10,lambda=1)
est.utpn(y)

tpn documentation built on Sept. 28, 2023, 1:06 a.m.