tpn (version 1.8)

choose.fts: Choose a distribution in the flexible truncated positive class of models

Description

Provide model selection for a given data set in the flexible truncated positive class of models

Usage

choose.fts(y, criteria = "AIC")

Value

A list with the following components

AIC

a vector with the AIC for the different truncated positive fitted models: normal, laplace, cauchy and logistic.

selected

the selected model

estimate

the estimated for sigma and lambda and the respective standard errors (s.e.)

conv

the code related to the convergence for the optim function. 0 if the convergence was attached.

logLik

log-likelihood function evaluated in the estimated parameters.

AIC

Akaike's criterion.

BIC

Schwartz's criterion.

Arguments

y

positive vector of responses

criteria

model criteria for the selection: AIC (default) or BIC.

Author

Gallardo, D.I., Gomez, H.J. and Gomez, Y.M.

Details

The function fits the truncated positive normal, truncated positive laplace, truncated positive Cauchy and truncated positive logistic models and select the model which provides the lower criteria (AIC or BIC).

References

Gomez, H.J., Gomez, H.W., Santoro, K.I., Venegas, O., Gallardo, D.I. (2022). A Family of Truncation Positive Distributions. Submitted.

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=rfts(n=100,sigma=10,lambda=1,dist="logis")
choose.fts(y)