choose.compound {gentransmuted}R Documentation

Choose a compound distribution.

Description

choose.compound select a combination of baseline and compounding distributions in the class of compound distribution. See details for supported distributions.

Usage

choose.compound(x, type = "positive", criteria = "AIC")

Arguments

x

the vector of values to be fitted.

type

Support of the x's. Avaliable options: positive (default), unit, real.

criteria

model selection criteria to be applied for the selection. Avaliable options: AIC (default, Akaike's information criteria) and BIC (Bayesian's information criteria).

Details

The compound distribution has cumulative distribution function

F(x;\gamma,\beta,\theta_1,\theta_2)=G_2(G_1(F(x;\gamma,\beta),\theta_1),\theta_2),

where F is related to the baseline distribution and G_1, G_2 are related to compounding models. For positive values, the options assessed for F are exponential, gamma, log-normal, paretoII and Birnbaum-Saunders. For unit values, the options for F are beta and Kumaraswamy. For real values, the options for F are normal, logistic, Cauchy and Gumbel. For G_1 and G_2 are assessed all the combinations among the exponentiated, exponentiated of second kind, Marshall-Olkin, Marshall-Olkin of the second kind and

Value

A list containing the following components:

coefficients

A matrix with the estimates and standard errors.

logLik

The log-likelihood function evaluated in the estimated parameters

AIC

Akaike's Information Criterion

BIC

Bayesian's Information Criterion

Author(s)

Yolanda M. Gomez, Diego I. Gallardo, Hector W. Gomez and Barry Arnold

Examples

set.seed(2100)
y=rcompound(100, 1.2, 1.4, 1, 0.8, dist="exp", comp1="EXP", comp2="MO")

choose.compound(y, type="positive")


[Package gentransmuted version 1.0 Index]