On 11/7/2008 12:00 PM, Stephen Collins wrote:
I am simulating sickness among a group of families. Part of the task is
to randomly draw who in the family will be sick, randomly drawing from
family ID's where Dad =1, Mom = 2, Kid1 = 3, Kid2 = 4., etc. My census of
Dads is of the form shown below.
Dad_ID Spouse (Y=1;N=0) #Kids #People_Becoming_Sick
1 1 0 1
2 0 2 2
3 1 0 2
4 1 3 3
...
The end output needed is if 3 people in a family are to be sick, was it
the dad and two kids, with random family ID's = {1,3,4}, or the mom, dad,
and one kid, with random family ID's = {2,1,4}, etc.. The complication
is that length of the family ID's to choose from and the associated
sampling probabilities -- changes with each family. I could loop through
the Dads, from i in 1:nrow(census), but is there a way I could vectorize
sample() to get at the same objective?
My attempts to use the apply-based functions have dead ended. Other ideas
to vectorize this problem are warmly welcomed.
You might want to transform runif instead of using sample(). For
example, if you want to generate M integers from 1:n_i, where n_i varies
from sample to sample, you could use
gen <- ceiling(runif(M, 0, n))
(where n is a vector of length M giving the upper limits).
Duncan Murdoch
Regards,
Stephen Collins, MPP | Analyst
Health & Benefits | Aon Consulting
200 East Randolph, Suite 900, Chicago, IL
Tel: 312-381-2578 | Fax: 312-381-0136
Email: [EMAIL PROTECTED]
Aon Consulting selected by the readers of Business Insurance as the “Best
Employee Benefit Consulting Firm� in 2006, 2007, and 2008
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