normal.normal.mix {LearnBayes} | R Documentation |
Computes the parameters and mixing probabilities for a normal sampling problem, variance known, where the prior is a discrete mixture of normal densities.
normal.normal.mix(probs,normalpar,data)
probs |
vector of probabilities of the normal components of the prior |
normalpar |
matrix where each row contains the mean and variance parameters for a normal component of the prior |
data |
vector of observation and sampling variance |
probs |
vector of probabilities of the normal components of the posterior |
normalpar |
matrix where each row contains the mean and variance parameters for a normal component of the posterior |
Jim Albert
probs=c(.5, .5)
normal.par1=c(0,1)
normal.par2=c(2,.5)
normalpar=rbind(normal.par1,normal.par2)
y=1; sigma2=.5
data=c(y,sigma2)
normal.normal.mix(probs,normalpar,data)