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pfn
2012 Mar 10
1
Draw values from multiple data sets as inputs to a Monte-Carlo function; then apply across entire matrix
...I have (for simplicity) 3 spatial raster data sets (each 4848 x 4053
cells) as ASCII files:
-Poultry density (mean value in each cell)
-Poultry density (standard deviation in each cell)
-Wild bird density (single estimate in each cell)
I read them into R using read.table. The data look correct:
Pmn <- read.table("D:/Data/PoultryMeans.txt")
Psd <- read.table("D:/Data/PoultryStDev.txt")
Wde <- read.table("D:/Data/WildBirdDensity.txt")
The Model:
In the Monte-Carlo simulation, Poultry and Wild birds have different
distributions (normal and triangle, respe...
2010 Feb 08
0
Mixed logit models with a random coefficient
...andard deviations
b2<-theta[3] /*B2
P<-NULL
b1<-rnorm(500,mean=m1,sd=s1) /*generate 500 random draws for B1
for(m in 0:999)
{
Dm<-X[(1+3*m):(3+3*m),] /*Extract the data for one person
Pn<-NULL
for(n in 1:500)
{
b<-rbind(b1[n],b2)
an<-sum(exp(Dm%*%b))
Pmn<-exp(Dm%*%b)/an /*Under each B1, compute the choice
probabilities
Pn<-cbind(Pn,Pmn)
}
Pm<-rowMeans(Pn) /* The simulated probabilities for one person
P<-rbind(P,Pm) /* Obtain the choice probabilities for all 1,000 people
}
sum(log(P)*(as.numeric(y))) /* Log-likelihood func...