| sufficientStatistics.CatDirichlet | R Documentation |
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 is:
the effective counts of each unique label in x. i.e. T(x)[i] = sum(uniqueLabels[i]
## S3 method for class 'CatDirichlet' sufficientStatistics(obj, x, foreach = FALSE, ...)
obj |
A "CatDirichlet" object. |
x |
numeric,integer or character, samples of the Categorical distribution. |
foreach |
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.
CatDirichlet, sufficientStatistics_Weighted.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 sufficientStatistics(obj=obj,x=x,foreach = TRUE) #return the sample itself