sufficientStatistics_Weighted.CatDirichlet {bbricks}R Documentation

Weighted sufficient statistics of a "CatDirichlet" object


For following Categorical-Dirichlet model structure:

pi|alpha \sim Dir(alpha)

x|pi \sim Categorical(pi)

Where Dir() is the Dirichlet distribution, Categorical() is the Categorical distribution. See ?dDir and dCategorical for the definitions of these distribution.
the sufficient statistics of a set of samples x and weights w are:
the effective counts (in this case the sum of the weight w) of each unique label in x
Unique values of x must be in obj$gamma$uniqueLabels, where "obj" is a "CatDirichlet" object, see examples below.


## S3 method for class 'CatDirichlet'
sufficientStatistics_Weighted(obj, x, w, foreach = FALSE, ...)



A "CatDirichlet" object.


numeric,integer or character, samples of the Categorical distribution.


numeric, sample weights.


logical, specifying whether to return the sufficient statistics for each observation. Default FALSE.


Additional arguments to be passed to other inherited types.


An object of class "ssCat", the sufficient statistics of a set of categorical samples. Or an object of the same class as x if foreach=TRUE.


Murphy, Kevin P. Machine learning: a probabilistic perspective. MIT press, 2012.

See Also

sufficientStatistics.CatDirichlet CatDirichlet


obj <- CatDirichlet(gamma=list(alpha=runif(26,1,2),uniqueLabels = letters))
x <- sample(letters,size = 20,replace = TRUE)
w <- runif(20)
sufficientStatistics(obj=obj,x=x)       #return the counts of each unique label
sufficientStatistics_Weighted(obj=obj,x=x,w=w) #return the weighted counts of each unique lable

[Package bbricks version 0.1.4 Index]