BayesCPclust (version 0.1.0)

postK_mk: Marginal probability of K per bin

Description

Marginal probability of K per bin

Usage

postK_mk(k, m0, w, M, Yn, sigma2n, cellsn, mk, Cr)

Value

`postK_mk` returns a numerical value representing the non-normalized probability for a given bin, given k, and a given cluster

Arguments

k

A scalar for the number of changes points in a cluster

m0

A scalar for the number of positions available to define change-points positions

w

A scalar representing the minimum number of points in each interval between two change points

M

A scalar representing the number of points available for each data sequence

Yn

A vector or matrix with data sequences for a cluster

sigma2n

A vector with the variance of the data sequences in a cluster

cellsn

A vector with the indices of the data sequences in a cluster

mk

A matrix with all possible values to distribute between change points

Cr

A scalar with the number of data sequences in a cluster

See Also

[postK()], [gibbs_alg()]

Examples

data(data)
M <- 50; k <- 0; w <- 10;
m0 <- M - 1 -(k+1)*w
for(k in 0:2){
mk <- RcppAlgos::permuteGeneral(0:m0, k + 1,
constraintFun = "sum",
comparisonFun = "==", limitConstraints = m0,
repetition = TRUE)}
out <- postK_mk(k = 0, m0 = m0, w = 10, M = 50, Yn = data[,c(1,2,4)],
 sigma2n = rep(0.05, 3), cellsn = c(1,2,4), mk = mk[1,], Cr = 3)