unitquantreg (version 0.0.6)

likelihood_stats: Likelihood-based statistics of fit for unitquantreg objects.

Description

Computes the likelihood-based statistics (Neg2LogLike, AIC, BIC and HQIC) from unitquantreg objects.

Usage

likelihood_stats(..., lt = NULL)
# S3 method for likelihood_stats
print(x, ...)

Value

A list with class "likelihood_stats" containing the following components:

call

the matched call.

stats

ordered matrix according AIC value containg the likelihood based statistics.

Arguments

...

unitquantreg objects separated by commas. Not use in print method.

lt

a list with one or more unitquantreg objects.

x

object of class likelihood_stats obtained from likelihood_stats function.

Author

André F. B. Menezes

Josmar Mazucheli

Details

Neg2LogLike: The log-likelihood is reported as $$Neg2LogLike= -2\log(L)$$

AIC: The Akaike's information criterion (AIC) is defined as $$AIC = -2\log(L)+2p$$

BIC: The Schwarz Bayesian information criterion (BIC) is defined as $$BIC = -2\log(L) + p\log(n)$$

HQIC: The Hannan and Quinn information criterion (HQIC) is defined as $$HQIC = -2\log(L) + 2p\log[\log(n)]$$ where \(L\) is the likelihood function.

References

Akaike, H. (1974). A new look at the statistical model identification. IEEE Transaction on Automatic Control, 19(6), 716--723.

Hannan, E. J. and Quinn, B. G. (1979). The determination of the order of an autoregression. Journal of the Royal Statistical Society, Series B, 41(2), 190--195.

Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6(2), 461--464.

Examples

data(sim_bounded, package = "unitquantreg")
sim_bounded_curr <- sim_bounded[sim_bounded$family == "uweibull", ]

models <- c("uweibull", "kum", "ulogistic")
lt_fits <- lapply(models, function(fam) {
  unitquantreg(formula = y1 ~ x, tau = 0.5, data = sim_bounded_curr,
               family = fam)
})

ans <- likelihood_stats(lt = lt_fits)
ans