reports/postTreatment.R

   1 K <- list("2"=2, "5"=2, "10"=3)
   2 p <- list("2"=c(.5,.5), "5"=c(.5,.5), "10"=c(.3, .3, .4))
   3 b <- list("2"=c(-.2, .5), "5"=c(-.2, .5), "10"=c(-.2, 0, .5))
   4 beta <- list(
   5   "2"=matrix( c(1,-2, 3,1), ncol=2 ),
   6   "5"=matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=2 ),
   7   "10"=matrix( c(1,2,-1,0,3,4,-1,-3,0,2, 2,-3,0,1,0,-1,-4,3,2,0, -1,1,3,-1,0,0,2,0,1,-2), ncol=3 ))
   8
   9 for (n in c("5000", "10000", "100000")) {
  10   for (d in c("2", "5", "10")) {
  11     load(paste0("res_",n,"_",d,"_logit.RData"))
  12
  13     # p
  14     for (m in 1:2) {
  15       err <- c()
  16       for (i in 1:K[[d]])
  17         err <- c(err, mean(abs(morpheus:::.extractParam(mr, 1, i)[[1]] - p[[d]][i])))
  18       print(paste0("p", m, " ", mean(err)))
  19     }
  20
  21     # b
  22     for (m in 1:2) {
  23       err <- c()
  24       for (i in 1:K[[d]])
  25         err <- c(err, mean(abs(morpheus:::.extractParam(mr, 2+d, i)[[1]] - b[[d]][i])))
  26       print(paste0("b", m, " ", mean(err)))
  27     }
  28
  29     # beta
  30     for (m in 1:2) {
  31       for (i in 1:K[[d]]) {
  32         err <- c()
  33         for (j in 1:d)
  34           err <- c(err, mean(abs(morpheus:::.extractParam(mr, 1+j, i)[[1]] - beta[[d]][1+j,i])))
  35         print(paste0("beta", m, "_", i, " ", mean(err)))
  36       }
  37     }
  38   }
  39 }