luck: Generalized iLUCK models

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Generalized iLUCK-models are a way to define sets of priors based on conjugate priors, with the property that the set of posteriors, obtained by updating each prior in the set by Bayes' rule, is still easy to handle. Generalized iLUCK-models belong to the domain of imprecise probability (or interval probability models), allow to include non-stochastic uncertainty ('ambiguity') in Bayesian analysis, and lead to reasonable inferences in case of prior-data conflict.

Author
Gero Walter [aut, cre], Norbert Krautenbacher [aut]
Date of publication
2013-08-27 15:53:15
Maintainer
Gero Walter <Gero.Walter@stat.uni-muenchen.de>
License
Artistic-2.0
Version
0.9

View on R-Forge

Man pages

cdfplot-methods
Plot sets of cumulative density functions for 'LuckModel'...
ExponentialData-class
Class '"ExponentialData"' and its constructor function...
ExponentialLuckModel-class
Class '"ExponentialLuckModel"' and its constructor function...
is.samplesize
Function to check if the argument is a sample size, i.e., a...
LuckModel-class
Class '"LuckModel"' and its constructor function...
LuckModelData-class
Class '"LuckModelData"' and its constructor function...
luck-package
Generalized iLUCK Models for Bayesian Inference with Sets of...
OptionalMatrix-class
Class '"OptionalMatrix"'
plot-methods
Plotting canonical parameter sets
ScaledNormalData-class
Class '"ScaledNormalData"' and its constructor function...
ScaledNormalLuckModel-class
Class '"ScaledNormalLuckModel"' and its constructor function...
show-methods
Methods for printing LuckModel and LuckModelData objects of...
singleCdf-methods
Values of the cumulative density function
singleHdi-methods
Highest density intervals for 'LuckModel's
unionHdi-methods
Calculate the union of highest density intervals for...
updateLuckN
Calculate the posterior canonical parameter n^(n)
updateLuckY
Calculate the posterior canonical parameter y^(n)
wrapOptim
Function to address 'optim' and 'optimize' with the same set...

Files in this package

luck/DESCRIPTION
luck/NAMESPACE
luck/R
luck/R/00-01_LuckModelData.r
luck/R/00-02_LuckModel.r
luck/R/00-03_utilLuckModel.r
luck/R/00-04_unionHdiLuckModel.r
luck/R/00-05_plotLuckModel.r
luck/R/00-06_cdfplotLuckModel.r
luck/R/01-01_ScaledNormalData.r
luck/R/01-02_ScaledNormal.r
luck/R/02-01_ExponentialData.r
luck/R/02-02_Exponential.r
luck/inst
luck/inst/CITATION
luck/man
luck/man/ExponentialData-class.Rd
luck/man/ExponentialLuckModel-class.Rd
luck/man/LuckModel-class.Rd
luck/man/LuckModelData-class.Rd
luck/man/OptionalMatrix-class.Rd
luck/man/ScaledNormalData-class.Rd
luck/man/ScaledNormalLuckModel-class.Rd
luck/man/cdfplot-methods.Rd
luck/man/is.samplesize.Rd
luck/man/luck-package.Rd
luck/man/plot-methods.Rd
luck/man/show-methods.Rd
luck/man/singleCdf-methods.Rd
luck/man/singleHdi-methods.Rd
luck/man/unionHdi-methods.Rd
luck/man/updateLuckN.Rd
luck/man/updateLuckY.Rd
luck/man/wrapOptim.Rd
luck/tests
luck/tests/00-01_LuckModelData_Tests.R
luck/tests/00-01_LuckModelData_Tests.Rout
luck/tests/00-02_LuckModel_Tests.R
luck/tests/00-02_LuckModel_Tests.Rout
luck/tests/00-03_utilLuckModel_Tests.R
luck/tests/00-03_utilLuckModel_Tests.Rout
luck/tests/00-05_plotLuckModel_Tests.R
luck/tests/00-05_plotLuckModel_Tests.Rout
luck/tests/01-01_ScaledNormalData_Tests.R
luck/tests/01-01_ScaledNormalData_Tests.Rout
luck/tests/01-02_ScaledNormal_Tests.R
luck/tests/01-02_ScaledNormal_Tests.Rout
luck/tests/02-01_ExponentialData_Tests.R
luck/tests/02-01_ExponentialData_Tests.Rout
luck/tests/02-02_Exponential_Tests.R
luck/tests/02-02_Exponential_Tests.Rout