tpn (version 1.10)

est.utpn: 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)

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.

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.

Author

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)