使用R在一个面板中绘制贝叶斯先验和后验分布的解释

Question

Could someone explain with details how this code is working?

require(lattice)
?lattice  # essential reading

 data <- dgamma(seq(from=0.00001,to=0.01,by=0.00001),shape = .1, scale = .01)

dfrm <- data.frame(dgam = data, param="s.1.01")
dfrm <- rbind(dfrm, data.frame(dgam =
                                 dgamma( seq(from=0.00001,to=0.01,by=0.00001), 
                                 shape = .2, scale = .01), 
                               param="s.2.01") )
dfrm <- cbind( dfrm, X.val=seq(from=0.00001,to=0.01,by=0.00001) )
str(dfrm)
#'data.frame':  2000 obs. of  3 variables:
# $ dgam : num  5263 2817 1954 1507 1231 ...
# $ param: Factor w/ 2 levels "s.1.01","s.2.01": 1 1 1 1 1 1 1 1 1 1 ...
# $ X.val: num  1e-05 2e-05 3e-05 4e-05 5e-05 6e-05 7e-05 8e-05 9e-05 1e-04 ...
xyplot( dgam ~ X.val , 
        group=param, 
        data=dfrm, type="l")

For instance, In which part is specificating the prior and posterior?

I've found the code in the answer given here How to plot Bayesian prior and posterior distributions in one panel using R?

Answer 1

That answer only illustrates how to plot two curves in the same plot, but does not at all involve computing a true posterior given a prior and data. Namely, it just plots two Gamma distributions with shape=0.1 and shape=0.2 , and these are distinguished in the data frame by including a factor column param where "s.1.01" and "s.2.01" indicate the respective distributions.