inst/classic-bugs/vol1/kidney/kidney-data.R

In nimble: MCMC, Particle Filtering, and Programmable Hierarchical Modeling

"age" <-
structure(c(28, 48, 32, 31, 10, 16, 51, 55, 69, 51, 44, 34, 35, 
42, 17, 60, 60, 43, 53, 44, 46, 30, 62, 42, 43, 57, 10, 52, 53, 
54, 56, 50, 57, 44, 22, 42, 52, 60, 28, 48, 32, 32, 10, 17, 51, 
56, 69, 52, 44, 34, 35, 42, 17, 60, 60, 44, 53, 44, 47, 30, 63, 
43, 43, 58, 10, 52, 53, 54, 56, 51, 57, 45, 22, 42, 52, 60), .Dim = as.integer(c(38, 
2)))
"beta.dis" <-
c(0, NA, NA, NA)
"disease" <-
c(1, 2, 1, 1, 1, 1, 2, 2, 3, 2, 3, 1, 3, 3, 1, 3, 1, 1, 2, 1, 
4, 1, 3, 3, 3, 3, 2, 3, 2, 2, 3, 3, 4, 2, 1, 1, 4, 4)
"censored" <-
structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), .Dim = as.integer(c(38, 
2)))
"M" <-
2
"N" <-
38
"sex" <-
c(0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 
0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0)
"t" <-
structure(c(8, 23, 22, 447, 30, 24, 7, 511, 53, 15, 7, 141, 96, 
NA, 536, 17, 185, 292, NA, 15, 152, 402, 13, 39, 12, NA, 132, 
34, 2, 130, 27, NA, 152, 190, 119, NA, NA, 63, 16, NA, 28, 318, 
12, 245, 9, 30, 196, 154, 333, NA, 38, NA, NA, NA, 177, 114, 
NA, NA, 562, NA, 66, NA, 40, 201, 156, 30, 25, 26, 58, 43, 30, 
NA, 8, NA, 78, NA), .Dim = as.integer(c(38, 2)))
"t.cen" <-
structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 149, 0, 0, 
0, 0, 22, 0, 0, 0, 0, 0, 0, 113, 0, 0, 0, 0, 0, 5, 0, 0, 0, 54, 
6, 0, 0, 13, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 0, 70, 25, 4, 0, 0, 
159, 108, 0, 24, 0, 46, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 16, 
0, 8), .Dim = as.integer(c(38, 2)))