This class stores a Bayesian mixture model fitted by MCMC methods.
Objects from the Class
Objects can be created by calls of the form new("MixModelBayes", ...).
Slots
chains:
Object of class "list" storing the course of the Markov chains for each parameter.
mmData:
Object of class "numeric" storing the data.
configuration:
Object of class "list" storing
configuration. See notes for details.
results:
Object of class "list" storing results. See notes for details.
Extends
Class "MixModel", directly.
Methods
chains
signature(object = "MixModelBayes"): Gives
access to the chains slot of the object.
acceptanceRate
signature(object = "MixModelBayes"): Gives
the acceptance rate for the parameter of the Dirichlet distribution.
Acceptance rates between 0.3 and 0.7 are usually desired. Values
not smaller than 0.1 (not larger than 0.9) might still be
acceptable. The acceptance rate is only meaningful if the option
weightsPrior was set to the Finite-dimensional Dirichlet
prior.
Note
In addition to the content described in MixModel,
the following elements are present:
Slot configuration:
initsAs in MixModel.
priorsA list specifying the prior distributions for the
parameters of the components and the parameter of the Dirichlet
process.
chainA list with the technical specifications for the Markov
Chains.
Slot results is exactly like in MixModel.
Slot chains:
componentsA list giving the values for the parameters of the
components in each iteration after burn-in and application of thinning.
piA matrix giving the values for the weights pi of the
components in each iteration after burn-in and application of thinning.
dirichletParameterA vector giving the values for dirichlet
Parameter in each iteration after burn-in and application of thinning.
classificationA matrix giving the number of genes classified to
each components in each iteration after burn-in and application of thinning.
Author(s)
Hans-Ulrich Klein (h.klein@uni-muenster.de)
See Also
bayesMixModelMixModel
Examples
showClass("MixModelBayes")
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(epigenomix)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
rbind, rownames, sapply, setdiff, sort, table, tapply, union,
unique, unsplit
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Loading required package: S4Vectors
Loading required package: stats4
Attaching package: 'S4Vectors'
The following objects are masked from 'package:base':
colMeans, colSums, expand.grid, rowMeans, rowSums
Loading required package: IRanges
Loading required package: GenomicRanges
Loading required package: GenomeInfoDb
Loading required package: SummarizedExperiment
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/epigenomix/MixModelBayes-class.Rd_%03d_medium.png", width=480, height=480)
> ### Name: MixModelBayes-class
> ### Title: Class '"MixModelBayes"'
> ### Aliases: MixModelBayes-class chains chains,MixModelBayes-method
> ### acceptanceRate acceptanceRate,MixModelBayes-method
> ### Keywords: classes
>
> ### ** Examples
>
> showClass("MixModelBayes")
Class "MixModelBayes" [package "epigenomix"]
Slots:
Name: chains mmData configuration results
Class: list numeric list list
Extends: "MixModel"
>
>
>
>
>
> dev.off()
null device
1
>