mleCalc-methods: Methods for functions mceCalc and mleCalc in Package...
In distrMod: Object Oriented Implementation of Probability Models

mceCalc-methods

R Documentation

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`