Compositional (version 5.4)

Column-wise MLE of some univariate distributions: Column-wise MLE of some univariate distributions

Description

Column-wise MLE of some univariate distributions.

Usage

colbeta.est(x, tol = 1e-07, maxiters = 100, parallel = FALSE)
collogitnorm.est(x)
colunitweibull.est(x, tol = 1e-07, maxiters = 100, parallel = FALSE)
colsimplex.est(x, tol = 1e-07)

Arguments

x

A numerical matrix with data. Each column refers to a different vector of observations of the same distribution. The values must by percentages, exluding 0 and 1,

tol

The tolerance value to terminate the Newton-Fisher algorithm.

maxiters

The maximum number of iterations to implement.

parallel

Do you want to calculations to take place in parallel? The default value is FALSE

Value

A matrix with two or three columns. The first one or the first two contain the parameter(s) of the distribution and the second or third column the relevant log-likelihood.

Details

For each column, the same distribution is fitted and its parameters and log-likelihood are computed.

References

N.L. Johnson, S. Kotz \& N. Balakrishnan (1994). Continuous Univariate Distributions, Volume 1 (2nd Edition).

N.L. Johnson, S. Kotz \& N. Balakrishnan (1970). Distributions in statistics: continuous univariate distributions, Volume 2.

J. Mazucheli, A. F. B. Menezes, L. B. Fernandes, R. P. de Oliveira & M. E. Ghitany (2020). The unit-Weibull distribution as an alternative to the Kumaraswamy distribution for the modeling of quantiles conditional on covariates. Journal of Applied Statistics, DOI:10.1080/02664763.2019.1657813.

See Also

censpois.mle, gammapois.mle

Examples

# NOT RUN {
x <- matrix( rbeta(200, 3, 4), ncol = 4 )
a <- colbeta.est(x)
# }