abic.gen.exp: Akaike information criterion (AIC) and Bayesian information...

In reliaR: Comprehensive Tools for some Probability Distributions

Akaike information criterion (AIC) and Bayesian information criterion (BIC) for a sample from Generalized Exponential distribution

Description

The function abic.gen.exp() gives the loglikelihood, AIC and BIC values assuming an Generalized Exponential distribution with parameters alpha and lambda. The function is based on the invariance property of the MLE.

Usage

abic.gen.exp(x, alpha.est, lambda.est)

Arguments

x	vector of observations
alpha.est	estimate of the parameter alpha
lambda.est	estimate of the parameter lambda

Value

The function abic.gen.exp() gives the loglikelihood, AIC and BIC values.

References

Claeskens, G. and Hjort, N. L. (2008). Model Selection and Model Averaging, Cambridge University Press, London.

See Also

pp.gen.exp for PP plot and qq.gen.exp for QQ plot

Examples

## Load data set
data(bearings)
## Estimates of alpha & lambda using 'maxLik' package
## alpha.est = 5.28321139, lambda.est = 0.03229609
abic.gen.exp(bearings, 5.28321139, 0.03229609)

reliaR documentation built on Nov. 5, 2025, 6:57 p.m.