# BUGS with very large sample size

I posted this question on the JAGS help discussion, I was seeing if I could get any help here:

I wish to fit a survival model using the data below (first two columns are time points, NA represents censoring, third column is number of samples). Is there a way to weight the likelihood by the sample size?

If not, I could repeat each time point for given sample size but this would result in probably too larger of an overall sample.

a1=matrix(c(
0.01, 1, 463,
1, 2, 369,
9, 10, 116,
10, 11, 163,
11, 12, 149,
12, 13, 230,
12.5, NA, 150054,
11.5, NA, 146349,
10.5, NA, 118098,
9.5, NA, 41633,
8.5, NA, 30308,
7.5, NA, 25934,
6.5, NA, 29427,
2.5, NA, 37997,
1.5, NA, 40599,
0.5, NA, 43300),ncol=3,byrow=T)