mceCalc-methods {distrMod}

Methods for functions mceCalc and mleCalc in Package ‘distrMod’

Description

Methods for functions mceCalc and mleCalc in package distrMod;

Usage

mceCalc(x, PFam, ...)
mleCalc(x, PFam, ...)
## S4 method for signature 'numeric,ParamFamily'
mceCalc(x, PFam, criterion, 
                   startPar = NULL, penalty = 1e20, crit.name,
                   Infos = NULL, validity.check = TRUE,
                   withthetaPar = FALSE,...)
## S4 method for signature 'numeric,ParamFamily'
mleCalc(x, PFam, startPar = NULL, 
                   penalty = 1e20, dropZeroDensity = TRUE, Infos = NULL,
                    validity.check = TRUE, ...)
## S4 method for signature 'numeric,BinomFamily'
mleCalc(x, PFam, ...)
## S4 method for signature 'numeric,PoisFamily'
mleCalc(x, PFam, ...)
## S4 method for signature 'numeric,NormLocationFamily'
mleCalc(x, PFam, ...)
## S4 method for signature 'numeric,NormScaleFamily'
mleCalc(x, PFam, ...)
## S4 method for signature 'numeric,NormLocationScaleFamily'
mleCalc(x, PFam, ...)

Arguments

x

numeric; data at which to evaluate the estimator

PFam

an object of class ParamFamily; the parametric family at which to evaluate the estimator

criterion

a function measuring the “goodness of fit”

startPar

in case optim is used: a starting value for the parameter fit; in case optimize is used: a vector containing a search interval for the (one-dim) parameter

penalty

numeric; penalizes non-permitted parameter values

crit.name

character; the name of the criterion; may be missing

withthetaPar

logical; shall Parameter theta be transmitted?

Infos

matrix; info slot to be filled in object of class MCEstimate; may be missing

validity.check

logical: shall return parameter value be checked for validity?

dropZeroDensity

logical of length 1; shall observations with density zero be dropped? Optimizers like optim require finite values, so get problems when negative loglikelihood is evaluated.

...

additional argument(s) for optim / optimize

Details

mceCalc is used internally by function MCEstimator to allow for method dispatch according to argument PFam; similarly, and for the same purpose mleCalc is used internally by function MLEstimator. This way we / or any other developper can write particular methods for special cases where we may avoid using numerical optimization without interfering with existing code. For programming one's own mleCalc / mceCalc methods, there is the helper function meRes to produce consistent return values.

Value

a list with components

estimate

— the estimate as a named vector of numeric

criterion

— the criterion value (i.e.; a numeric of length 1); e.g. the neg. log likelihood

est.name

— the name of the estimator

param

— estimate coerced to class ParamFamParameter

crit.fct

— a function with the named components of theta as arguments returning the criterion value; used for profiling / coercing to class mle

method

— a character reporting how the estimate was obtained, i.e., by optim, by optimize or by explicit calculations

crit.name

character; the name of the criterion; may be ""

Infos

matrix; info slot to be filled in object of class MCEstimate; may be NULL

samplesize

numeric; sample size of x