Column-wise MLE of some univariate distributions
Column-wise MLE of some univariate distributions.
collognorm.mle(x) collogitnorm.mle(x) colborel.mle(x) colhalfnorm.mle(x) colordinal.mle(x, link = "logit") colcauchy.mle(x, tol = 1e-07, maxiters = 100, parallel = FALSE) colbeta.mle(x, tol = 1e-07, maxiters = 100, parallel = FALSE) colunitweibull.mle(x, tol = 1e-07, maxiters = 100, parallel = FALSE)
x |
A numerical matrix with data. Each column refers to a different vector of observations of the same distribution. The values of for Lognormal must be greater than zero, for the logitnormal they must by percentages, exluding 0 and 1, whereas for the Borel distribution the x must contain integer values greater than 1. For the halfnormal the numbers must be strictly positive, while for the ordinal this can be a numerical matrix with values 1, 2, 3,..., not zeros. |
link |
This can either be "logit" or "probit". It is the link function to be used. |
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 |
For each column, the same distribution is fitted and its parameters and log-likelihood are computed.
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. For the ordinal a list including:
param |
A matrix with the intercepts (threshold coefficients) of the model applied to each column (or variable). |
loglik |
The log-likelihood values. |
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Stefanos Fafalios stefanosfafalios@gmail.com.
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.
Agresti, A. (2002) Categorical Data. Second edition. Wiley.
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
x <- matrix( exp( rnorm(1000 * 50) ), ncol = 50) a <- collognorm.mle(x) x <- NULL
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