Displaying 6 results from an estimated 6 matches for "rmultinomial".
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multinomial
2008 Mar 18
2
rmultinomial() function
After scouring the online R resources and help pages, I still need clarification on the function rmultinomial(). I would like to create a vector, say of 100 elements, where every element in the vector can take on the value of 0, 1 or 2, and where each of those values have a specific probability. ie. the probability a given element in the vector = 0 is 0.06, 1 = 0.38, 2 = 0.56 (probabilities sum to 1). Can...
2010 Nov 18
1
dmultinomial
...multinomial(x=c(0,0,1),prob=c(1,1,1),size=1,log=TRUE)
Error in if (ncol(x) != K) stop("x[] and prob[] must be equal length
vectors or equal col matrix.") :
argument is of length zero
# Once I get the simple stuff above running, I'd like to be able to do
the following:
> testmat=rmultinomial(4, 1, prob)
> testmat
[,1] [,2] [,3]
[1,] 1 0 0
[2,] 0 0 1
[3,] 0 0 1
[4,] 0 0 1
> dmultinomial(x=testmat,prob=prob,size=1,log=TRUE)
Error in if (!is.null(size) && nrow(size) != n) size <- matrix(t(size), :
missing value where TRUE/FALSE...
2010 Mar 24
1
with data in the form of an R data objecte: Monte Carlo simulation in R
Hi, please use the following the matrix z as the example:
x<-c(2,4,5,7,6,9,8,2,0)
y<-matrix(x,3,3)
z<-apply(y,2,function(x)x/sum(x))
z
On Tue, Mar 23, 2010 at 6:59 PM, David Winsemius <dwinsemius@comcast.net>wrote:
>
> On Mar 23, 2010, at 9:05 PM, Hongwei Dong wrote:
>
> Hi, R-helpers,
>>
>> I'm trying to use R to do a Monte Carlo simulation and
2012 Aug 17
0
install.packages umask configuration
...package ?combinat?
finding HTML links ... done
combn html
dmnom html
hcube html
nsimplex html
permn html
rmultinomial html
x2u html
xsimplex html
** building package indices
** testing if installed package can be loaded
* DONE (combinat)
The downloaded source packages are in
?/tmp/RtmpYRQ6Gh/downloaded_packages...
2012 Oct 05
2
problem with convergence in mle2/optim function
...ncol = 3))
}
pdat <- sapply(tv, psim, simplify = TRUE)
Pdat <- as.data.frame(t(pdat))
names(Pdat) <- c("time", "P1", "P2", "P3")
# Generate simulated data set from probabilities
n = rep(20, length(tv))
p = as.matrix(Pdat[,2:4])
y <- as.data.frame(rmultinomial(n,p))
yt <- cbind(tv, y)
names(yt) <- c("tv", "n1", "n2", "n3")
# mle2 call
mle.fit <- mle2(NLL.func, data = list(y = yt),
start = list(p1 = p1t, p2 = p2t, mu1 = mu1t, mu2 = mu2t),
control = list(maxit = 5000, factr...
2012 Sep 27
0
problems with mle2 convergence and with writing gradient function
...3))
}
pdat <- sapply(tv, psim, simplify = TRUE)
Pdat <- as.data.frame(t(pdat))
names(Pdat) <- c("time", "P1", "P2", "P3")
# Generate simulated data set from model probabilities
n = rep(20, length(tv))
p = as.matrix(Pdat[,2:4])
y <- as.data.frame(rmultinomial(n,p))
yt <- cbind(tv, y)
names(yt) <- c("tv", "n1", "n2", "n3")
# mle2 call
mle.fit <- mle2(NLL.func, data = list(y = yt),
start = list(p1 = p1t, p2 = p2t, mu1 = mu1t, mu2 = mu2t),
control = list(maxit = 5000, lmm =...