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#PSEUDO BAYESIAN ESTIMATOR
getAlphaVector <- function(raw, apriori){
v_i <- rowSums(raw)
K_i <- numeric(nrow(raw))
sumSquaredY <- rowSums(raw^2)
#get numerator
K_i_num <- v_i^2-sumSquaredY
#get denominator
VQ <- matrix(0,nrow= nrow(apriori),ncol=ncol(apriori))
for (i in 1:nrow(VQ)) {
VQ[i,]<-v_i[i]*apriori[i,]
}
K_i_den<-rowSums((raw - VQ)^2)
K_i <- K_i_num/K_i_den
#get the alpha vector
alpha <- K_i / (v_i+K_i)
#empirical transition matrix
Emp<-raw/rowSums(raw)
#get the estimate
out<-matrix(0, nrow= nrow(raw),ncol=ncol(raw))
for (i in 1:nrow(out)) {
out[i,]<-alpha[i]*apriori[i,]+(1-alpha[i])*Emp[i,]
}
return(out)
}
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