On Mon, Oct 4, 2010 at 10:44 AM, Gabriela Cendoya
<gabrielacendoya.rl...@gmail.com> wrote:
> You are missing "s" in your definitions so I can't reproduce your code.
When he uses apply(), he sets s = 1.
>
>> tmp <- data.frame(var1 = sample(c(0:10), 3, replace = TRUE), var2 =
>> sample(c(0:10), 3, replace = TRUE), var3 = sample(c(0:10), 3, replace =
>> TRUE))
>>
>> str(tmp)
> 'data.frame': 3 obs. of 3 variables:
> $ var1: int 9 3 9
> $ var2: int 4 6 2
> $ var3: int 2 9 3
>>
>> #I can run the following double loop and yield what I want in the end (rr1)
>> as:
>>
>> library(statmod)
>> Q <- 2
>> b <- runif(3)
>> qq <- gauss.quad.prob(Q, dist = 'normal', mu = 0, sigma=1)
>> rr1 <- matrix(0, nrow = Q, ncol = nrow(tmp))
>> L <- nrow(tmp)
>> for(j in 1:Q){
> + for(i in 1:L){
> + rr1[j,i] <- exp(sum(log((exp(tmp[i,]*(qq$nodes[j]-b))) /
> (factorial(tmp[i,]) *
> + exp(exp(qq$nodes[j]-b)))))) * ((1/(s*sqrt(2*pi))) *
> exp(-((qq$nodes[j]-0)^2/(2*s^2))))/dnorm(qq$nodes[j]) * qq$weights[j]
> + }
> + }
> Error: objeto 's' no encontrado
>> rr1
> [,1] [,2] [,3]
> [1,] 0 0 0
> [2,] 0 0 0
>>
>
> Gabriela
>
>
> 2010/10/4, Doran, Harold <hdo...@air.org>:
>> Suppose I have the following data:
>>
>> tmp <- data.frame(var1 = sample(c(0:10), 3, replace = TRUE), var2 =
>> sample(c(0:10), 3, replace = TRUE), var3 = sample(c(0:10), 3, replace =
>> TRUE))
>>
>> I can run the following double loop and yield what I want in the end (rr1)
>> as:
>>
>> library(statmod)
>> Q <- 2
>> b <- runif(3)
>> qq <- gauss.quad.prob(Q, dist = 'normal', mu = 0, sigma=1)
>> rr1 <- matrix(0, nrow = Q, ncol = nrow(tmp))
>> L <- nrow(tmp)
>> for(j in 1:Q){
>> for(i in 1:L){
>> rr1[j,i] <-
>> exp(sum(log((exp(tmp[i,]*(qq$nodes[j]-b))) / (factorial(tmp[i,]) *
>> exp(exp(qq$nodes[j]-b)))))) *
>>
>> ((1/(s*sqrt(2*pi))) * exp(-((qq$nodes[j]-0)^2/(2*s^2))))/dnorm(qq$nodes[j])
>> * qq$weights[j]
>> }
>> }
>> rr1
>>
>> But, I think this is so inefficient for large Q and nrow(tmp). The function
>> I am looping over is:
>>
>> fn <- function(x, nodes, weights, s, b) {
>> exp(sum(log((exp(x*(nodes-b))) / (factorial(x) *
>> exp(exp(nodes-b)))))) *
>> ((1/(s*sqrt(2*pi))) *
>> exp(-((nodes-0)^2/(2*s^2))))/dnorm(nodes) * weights
>> }
>>
>> I've tried using apply in a few ways, but I can't replicate rr1 from the
>> double loop. I can go through each value of Q one step at a time and get
>> matching values in the rr1 table, but this would still require a loop and
>> that I think can be avoided.
>>
>> apply(tmp, 1, fn, nodes = qq$nodes[1], weights = qq$weights[1], s = 1, b =
>> b)
>>
>> Does anyone see an efficient way to compute rr1 without a loop?
>>
>> Harold
>>
>>> sessionInfo()
>> R version 2.10.1 (2009-12-14)
>> i386-pc-mingw32
>>
>> locale:
>> [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United
>> States.1252 LC_MONETARY=English_United States.1252
>> [4] LC_NUMERIC=C LC_TIME=English_United
>> States.1252
>>
>> attached base packages:
>> [1] stats graphics grDevices utils datasets methods base
>>
>> other attached packages:
>> [1] minqa_1.1.9 Rcpp_0.8.6 MiscPsycho_1.6 statmod_1.4.6
>> lattice_0.17-26 gdata_2.8.0
>>
>> loaded via a namespace (and not attached):
>> [1] grid_2.10.1 gtools_2.6.2 tools_2.10.1
>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>
> --
> _________________________
> Lic. María Gabriela Cendoya
> Magíster en Biometría
> Profesor Adjunto
> Facultad de Ciencias Agrarias
> UNMdP - Argentina
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/
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