Hello,

Where is the problem in this programming. I want two way matrix, but it gives problem.
The program is given below:


rep = 2
genes = 5
pred = c()
iter   = array (dim = c(rep, pred))
pred =
array(dim = c(1, genes))
m = c()
l = 1
w = 1
for(m in
1:rep) {
                                               
                                                                              t
= time data
                                                                              c
= cens
                                                                              tab
= cbind(t, c)
#
Resampling Time and Censoring
cc =
sample(c, replace = TRUE)                                 #
Bootstrap WR Censoring Data
tt =
sample(t, replace = TRUE)                                  #
Bootstrap WR Time Data
xx =
Surv(tt, cc)                                                                              #
Survival Times with Censored
 
 
 
P = predic[,1:5]                                                               # First 5 Rows of predic
n = 310                                                                                #
Every Row has 310 values
ma =
matrix(P, n)                                                           #
P cross n, matrix
 boot <- sample(seq(n), replace=TRUE)                               #
Bootstrap WR in seq(n)
 genes5 = ma[boot, ]                                                    # 5 genes Bootstrap
Matrix
 
 
 
 
                               for(p in 1: genes){
                                                                              i
= c()
                                               
                                                                              for(i
in w:l) {
                                                                                                              z
= genes5[,w: l]
                                                                                                              y
= coxph(xx ~ z)
                                                                                               
                                                                                                              }
                                                               Pval
= summary(y) $ coeff[, 5]
 
                                                               if( any(Pval <= 0.01) )                    sign <- 1               else        sign <- 0
                                                               pred[1,
p] = sign[1]
                                                                                                              }
iter [m, 1:5]
=        pred[1: 5]
 
}
 
Thanks in advance.

Regards
Fazli Raziq
	[[alternative HTML version deleted]]

