Methods for Function mle in Package ‘MAINT.Data’

Description

Performs maximum likelihood estimation for parametric models of interval data

Usage

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## S4 method for signature 'IData'
mle(Idt, Model=c("Normal","SKNormal","NrmandSKN"), CovCase=1:4,
  SelCrit=c("BIC","AIC"), OptCntrl=list(), ...)

Arguments

Idt

An IData object representing interval-valued entities.

Model

The joint distribution assumed for the MidPoint and LogRanges. Current alternatives are “Normal” for Gaussian, distributions, “SNNormal” for Skew-Normal and “NrmandSKN” for both Gaussian and Skew-Normal distributions.

CovCase

Configuration of the variance-covariance matrix: a set of integers between 1 and 4.

SelCrit

The model selection criterion.

OptCntrl

List of optional control parameters to passed to the optimization routine. See the documentation of RepLOptim for a description of the available options.

...

Other named arguments.

References

Brito, P., Duarte Silva, A. P. (2012): "Modelling Interval Data with Normal and Skew-Normal Distributions". Journal of Applied Statistics, Volume 39, Issue 1, 3-20.

See Also

IData, RepLOptim

Examples

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# Create an Interval-Data object containing the intervals of temperatures by quarter 
# for 899 Chinese meteorological stations.

ChinaT <- IData(ChinaTemp[1:8])

# Estimate parameters by maximum likelihood, assuming that one of 
# the C2, C3 or C4 restricted Covariance configurations holds

ChinaE <- mle(ChinaT,CovCase=2:4)
cat("China maximum likelhiood estimation results =\n")
print(ChinaE)
cat("Standard Errors of Estimators:\n")
print(stdEr(ChinaE))

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