estimate.compound {gentransmuted} | R Documentation |
Fitting a compound distribution.
Description
estimate.compound computes the maximum likelihood estimates for a compound distribution. See arguments for supported distributions.
Usage
estimate.compound(x, dist = "exp", comp1 = as.null(), comp2 = as.null(), est.var = TRUE)
Arguments
x |
the vector of values to be fitted. |
dist |
baseline distribution. Avaliable options: exp (exponential), gamma, lnorm (log-normal), paretoII, bisa (Birnbaum-Saunders), lomax, beta, kumar (Kumaraswamy), norm (normal), logis (logistic), cauchy, gumbel. See details for parameterizations of these distributions. |
comp1 , comp2 |
compounding distributions. Avaliable options: EXP (Exponentiated), EXP2 (Exponentiated of the second kind), MO (Marshall-Olkin), MO2 (Marshall-Olkin of the second kind), SB (Shaw and Buckley). |
est.var |
Logical. If TRUE the standard errors are estimated. |
Details
The parameterization for the different distributions is given in .
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")
estimate.compound(y, dist="exp", comp1="EXP", comp2="MO")