Column-wise MLE of distributions defined in the (0, 1) interval {MLE} | R Documentation |
Column-wise MLE of distributions defined in the (0, 1) interval
Description
Column-wise MLE of distributions defined in the (0, 1) interval.
Usage
colprop.mle(x, distr = "beta", tol = 1e-07, maxiters = 100, parallel = FALSE)
Arguments
x |
A numerical vector with proportions, i.e. numbers in (0, 1) (zeros and ones are not allowed). |
distr |
The distribution to fit. "beta" stands for the beta distribution, "logitnorm" is the logistic normal, "unitweibull" is the unit-Weibull and the "sp" is the standard power distribution. |
tol |
The tolerance level up to which the maximisation stops. |
maxiters |
The maximum number of iterations the Newton-Raphson will perform. |
parallel |
Should the computations take place in parallel? This is for the "spml" only. |
Details
Maximum likelihood estimation of the parameters of the beta distribution is performed via Newton-Raphson. The distributions and hence the functions does not accept zeros. "logitnorm.mle" fits the logistic normal, hence no nwewton-Raphson is required and the "hypersecant01.mle" uses the golden ratio search as is it faster than the Newton-Raphson (less calculations).
Value
A matrix with two, columns. The first one contains the parameters of the distribution and the second columns contains the log-likelihood values.
Author(s)
Michail Tsagris and Sofia Piperaki.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Sofia Piperaki sofiapip23@gmail.com.
References
N.L. Johnson, S. Kotz and N. Balakrishnan (1994). Continuous Univariate Distributions, Volume 1 (2nd Edition).
N.L. Johnson, S. Kotz and N. Balakrishnan (1970). Distributions in statistics: continuous univariate distributions, Volume 2.
J. Mazucheli, A. F. B. Menezes, L. B. Fernandes, R. P. de Oliveira and 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, 47(6): 954–974.
See Also
Examples
x <- rbeta(1000, 1, 4)
prop.mle(x, distr = "beta")