MLE (version 1.5)

Column-wise MLE of some censored models: Column-wise MLE of some censored models

Description

Column-wise MLE of some censored models.

Usage

colcens.mle(x, distr = "censweibull", di, tol = 1e-07, parallel = FALSE, cores = 0)

Value

A matrix with two, three or four 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.

Arguments

x

A vector with positive valued data and zero values. If there are no zero values, a simple normal model is fitted in the end.

distr

The distribution to fit. "censweibull" for the censored Weibull, "censpois" for the left censored Poisson and "tobit for the Tobit model. For the "censpois" the lowest value in x is taken as the censored point and values below that number are considered to be censored.

di

A vector of 0s (censored) and 1s (not censored) values.

tol

The tolerance level up to which the maximisation stops; set to 1e-07 by default.

parallel

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

cores

In case you set parallel = TRUE, then you need to specify the number of cores.

Author

Michail Tsagris, Sofia Piperaki and Nikolaos Kontemeniotis.

R implementation and documentation: Michail Tsagris and Sofia Piperaki and Nikolaos Kontemeniotis .

Details

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

References

Tobin James (1958). Estimation of relationships for limited dependent variables. Econometrica. 26(1): 24--36.

https://en.wikipedia.org/wiki/Tobit_model

Fritz Scholz (1996). Maximum Likelihood Estimation for Type I Censored Weibull Data Including Covariates. Technical report. ISSTECH-96-022, Boeing Information & Support Services, P.O. Box 24346, MS-7L-22.

See Also

cens.mle, colpositive.mle, colreal.mle

Examples

x1 <- matrix( rpois(1000 * 10, 15), ncol = 10)
x <- x1
x[x <= 10] <- 10
colMeans(x) ## simple Poisson
colcens.mle(x, distr = "censpois")