distrMod-package: distrMod -- probability models

Description

Based on the packages distr and distrEx package distrMod provides a flexible framework which allows computation of estimators like maximum likelihood or minimum distance estimators for probability models.

Arguments

Classes

[*]: there is a generating function with the same name ##########################
ProbFamily classes
##########################
slots: [()] 
name(character), distribution(Distribution),
distrSym(DistributionSymmetry), props(character) "ProbFamily"
|>"ParamFamily"     [*] 
additional slots:
param(ParamFamParameter), modifyParam(function),
startPar(function), makeOKPar(function), fam.call(call)
|>|>"L2ParamFamily" [*]
additional slots:
L2deriv(EuclRandVarList), L2deriv.fct(function), 
L2derivSymm(FunSymmList), L2derivDistr(DistrList),
L2derivDistrSymm(DistrSymmList), FisherInfo(PosSemDefSymmMatrix),
FisherInfo.fct(function)
|>|>|>"BinomFamily" [*]
|>|>|>"PoisFamily"  [*]
|>|>|>"BetaFamily"  [*]
|>|>|>"L2GroupParamFamily"
additional slots:
LogDeriv(function)
|>|>|>|>"L2ScaleShapeUnion"  /VIRTUAL/
|>|>|>|>|>"GammaFamily" [*]
|>|>|>|>"L2LocationScaleUnion"  /VIRTUAL/
additional slots:
locscalename(character)
|>|>|>|>|>"L2LocationFamily"            [*]
|>|>|>|>|>|>"NormLocationFamily"        [*] 
|>|>|>|>|>"L2ScaleFamily"               [*]
|>|>|>|>|>|>"NormScaleFamily"           [*] 
|>|>|>|>|>|>"ExpScaleFamily"            [*] 
|>|>|>|>|>|>"LnormScaleFamily"          [*] 
|>|>|>|>|>"L2LocationScaleFamily"       [*]
|>|>|>|>|>|>"NormLocationScaleFamily"   [*] 
|>|>|>|>|>|>"CauchyLocationScaleFamily" [*] and a (virtual) class union "L2ScaleUnion"  between
   "L2LocationScaleUnion"  and "L2ScaleShapeUnion" ##########################
ParamFamParameter
##########################
"ParamFamParameter" [*] is subclass of class "Parameter" of package "distr".
Additional slots:
main(numeric), nuisance(OptionalNumeric), fixed(OptionalNumeric),
trafo(MatrixorFunction) ##########################
Class unions
##########################
"MatrixorFunction" = union("matrix", "OptionalFunction")
"PrintDetails" = union("Estimate", "Confint", 
                   "PosSemDefSymmMatrix",
                   "ParamFamParameter", "ParamFamily") ##########################
Symmetry classes            (other classes moved to package "distr")
##########################
slots:
type(character), SymmCenter(ANY) "Symmetry"   (from package "distr")
|>"FunctionSymmetry"
|>|>"NonSymmetric"      [*]
|>|>"EvenSymmetric"     [*]
|>|>"OddSymmetric"      [*] list thereof
"FunSymmList"           [*] ##########################
Matrix classes              (moved to package "distr")
##########################
slots:
none
"PosSemDefSymmMatrix" [*] is subclass of class "matrix" of package "base".
|>"PosDefSymmMatrix"  [*] ##########################
Norm Classes
##########################
slots:
name(character), fct(function) "NormType"        [*]
|>"QFNorm"        [*]
Additional slots:
QuadForm(PosSemDefSymmMatrix)
|>|>"InfoNorm"    [*]
|>|>"SelfNorm"    [*] ##########################
Bias Classes
##########################
slots:
name(character) "BiasType"
|>"symmetricBias"   [*]
|>"onesidedBias"
Additional slots:
sign(numeric)
|>"asymmetricBias"  [*]
Additional slots:
nu(numeric) ##########################
Risk Classes
##########################
slots:
type(character) "RiskType"
|>"asRisk"
|>|>"asCov"       [*]
|>|>"trAsCov"     [*]
|>"fiRisk"
|>|>"fiCov"       [*]
|>|>"trfiCov"     [*]
|>|>"fiHampel"    [*]
Additional slots:
bound(numeric)
|>|>"fiMSE"       [*]
|>|>"fiBias"      [*]
|>|>"fiUnOvShoot" [*]
Additional slots:
width(numeric) Risk with Bias:
"asRiskwithBias"
slots: biastype(BiasType), normtype(NormType),
|>"asHampel"      [*]
Additional slots:
bound(numeric)
|>"asBias"        [*]
|>"asGRisk"
|>|>"asMSE"       [*]
|>|>"asUnOvShoot" [*]
Additional slots:
width(numeric)
|>|>"asSemivar"   [*] ##########################
Estimate Classes
##########################
slots:
name(character), estimate(ANY),
samplesize(numeric), asvar(OptionalMatrix),
Infos(matrix), nuis.idx(OptionalNumeric)
fixed.estimate(OptionalNumeric), 
estimate.call(call), trafo(list[of function, matrix]),
untransformed.estimate(ANY), 
untransformed.asvar(OptionalMatrix)
criterion.fct(function), method(character), "Estimate"
|>"MCEstimate", 
Additional slots:
criterion(numeric) ##########################
Confidence interval class
##########################
slots:
type(character), confint(array),
estimate.call(call), name.estimate(character),
trafo.estimate(list[of function, matrix]), 
nuisance.estimate(OptionalNumeric)
"Confint"

Methods

besides accessor and replacement functions, we have methods solve, sqrt for matrices checkL2deriv, existsPIC for class L2ParamFamily LogDeriv for class L2GroupParamFamily validParameter for classes ParamFamily, L2ScaleFamily, L2LocationFamily, and L2LocationScaleFamily modifyModel for the pairs of classes L2ParamFamily and ParamFamParameter, L2LocationFamily and ParamFamParameter, L2ScaleFamily and ParamFamParameter, L2LocationScaleFamily and ParamFamParameter, GammaFamily and ParamFamParameter, and ExpScaleFamily and ParamFamParameter mceCalc for the pair of classes numeric and ParamFamily mleCalc for the pairs of classes numeric and ParamFamily, numeric and BinomFamily, numeric and PoisFamily, numeric and NormLocationFamily, numeric and NormScaleFamily, and numeric and NormLocationScaleFamily coerce from class MCEstimate to class mle confint for class Estimate profile for class MCEstimate

Functions

Management of global options:
"distrModOptions", "distrModoptions", "getdistrModOption", check for ker of matrix: "isKerAinKerB" particular norms: "EuclideanNorm", "QuadFormNorm"
onesided bias: "positiveBias", "negativeBias", Estimators:
"Estimator", "MCEstimator", "MLEstimator", "MDEstimator" special location/scale models:
"L2LocationUnknownScaleFamily", "L2ScaleUnknownLocationFamily" some special normal models:
"NormScaleUnknownLocationFamily", "NormLocationUnknownScaleFamily",

Start-up-Banner

You may suppress the start-up banner/message completely by setting options("StartupBanner"="off") somewhere before loading this package by library or require in your R-code / R-session. If option "StartupBanner" is not defined (default) or setting options("StartupBanner"=NULL) or options("StartupBanner"="complete") the complete start-up banner is displayed. For any other value of option "StartupBanner" (i.e., not in c(NULL,"off","complete")) only the version information is displayed. The same can be achieved by wrapping the library or require call into either suppressStartupMessages() or onlytypeStartupMessages(.,atypes="version"). As for general packageStartupMessage's, you may also suppress all the start-up banner by wrapping the library or require call into suppressPackageStartupMessages() from startupmsg-version 0.5 on.

Demos

Demos are available --- see demo(package="distrMod").

Scripts

Example scripts are available --- see folder ‘scripts’ in the package folder to package distrMod in your library.

Package versions

Note: The first two numbers of package versions do not necessarily reflect package-individual development, but rather are chosen for the distrXXX family as a whole in order to ease updating "depends" information.

Details

Package:

distrMod

Version:

2.5

Date:

2013-09-11

Depends:

R(>= 2.6.0), methods, startupmsg, distr(>= 2.2), distrEx(>= 2.2), RandVar(>= 0.6.3), MASS, stats4

LazyLoad:

yes

License:

LGPL-3

URL:

http://distr.r-forge.r-project.org/

SVNRevision:

904

References

M. Kohl and P. Ruckdeschel (2010): R Package distrMod: S4 Classes and Methods for Probability Models. Journal of Statistical Software, 35(10), 1-27. http://www.jstatsoft.org/v35/i10/ (see also vignette("distrMod"))

P. Ruckdeschel, M. Kohl, T. Stabla, F. Camphausen (2006): S4 Classes for Distributions, R News, 6(2), 2-6. http://CRAN.R-project.org/doc/Rnews/Rnews_2006-2.pdf

A vignette for packages distr, distrSim, distrTEst, and distrEx is included into the mere documentation package distrDoc and may be called by require("distrDoc");vignette("distr")