| est.utpn {tpn} | R Documentation |
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)