yfyang86 / kmc Goto Github PK

library(kmc)
library(Rcpp)
check_G_mat(matrix(rnorm(20),nrow=2))

library(KMsurv)
library(emplik)
data(kidney)
RMSTfun <- function(x) {pmin(x,20) - 15}
el.cen.EM2( x  = kidney$time, d = kidney$delta, fun = RMSTfun, mu = 0, maxit = 50)

$loglik
[1] -131.105

$times
 [1]  0.5  0.5  0.5  0.5  0.5  0.5  1.5  2.5  2.5  3.5  3.5  4.5  4.5  5.5  6.5
[16]  8.5  8.5  9.5 10.5 11.5 15.5 15.5 16.5 18.5 23.5 26.5 28.5

$prob
 [1] 0.01122308 0.01122308 0.01122308 0.01122308 0.01122308 0.01122308
 [7] 0.01243132 0.01279473 0.01279473 0.01381316 0.01381316 0.01533046
[13] 0.01533046 0.01599773 0.01746515 0.02043914 0.02043914 0.02186346
[19] 0.02285866 0.02485554 0.03538362 0.03538362 0.03297763 0.03220609
[25] 0.06200016 0.10114908 0.39333447

$lam
[1] 2.061926

$iters
[1] 50

$`-2LLR`
[1] 2.51874

$Pval
[1] 0.1125004

library(kmc)
kmc.solve(kidney$time, kidney$delta, list(RMSTfun))
myfun9 <- function(theta, x, d){
    ff <- function(t) pmin(t, 20) - theta
kmc.solve(x, d, g = list(ff)) 
}
findUL(step = 1, fun = myfun9, MLE = 16, x = kidney$time, d = kidney$delta)

$Low
[1] 12.97085

$Up
[1] 19.56962

$FstepL
[1] 6.103516e-05

$FstepU
[1] 8.69197e-05

$Lvalue
[1] 3.840001

$Uvalue
[1] -198.9877

Warning messages:
1: In kmc.solve(x, d, g = list(ff)) :
The results may be not feasible!

2: In kmc.solve(x, d, g = list(ff)) :
The results may be not feasible!

3: In kmc.solve(x, d, g = list(ff)) :
The results may be not feasible!

4: In kmc.solve(x, d, g = list(ff)) :
The results may be not feasible!

5: In kmc.solve(x, d, g = list(ff)) :
The results may be not feasible!

6: In kmc.solve(x, d, g = list(ff)) :
The results may be not feasible!

7: In kmc.solve(x, d, g = list(ff)) :
The results may be not feasible!