Displaying 2 results from an estimated 2 matches for "sums3".
Did you mean:
sums
2004 Mar 27
1
Re: [S] scalability
...I am not sure designers who
BR> add features take enough account of the costs.
Using R 1.8.1 (precompiled) on SuSe Linux with a Xeon 2.4GHz and 1G of
memory:
set.seed(2)
jja <- array(rnorm(3000*300*3), c(3000, 300, 3))
gc()
system.time(jjsa <- apply(jja, 1:2, sum)) # takes 30 seconds
sumS3 <- function(x, ...) UseMethod("sumS3")
sumS3.default <- function(x, ...) sum(x, ...)
gc()
system.time(jjsa3 <- apply(jja, 1:2, sumS3)) # takes 65 seconds
sumS4 <- function(x, ...) standardGeneric("sumS4")
setMethod("sumS4", signature(x="numeric")...
2011 May 26
0
'constrained' negative.binomial model estimates
...unt for over-dispersion (which may still exist even after
the constraint is imposed), however, the effect of the 'constraint'
factor does not seem to work, due likely to the additional theta
parameter.
> model3 <- glm.nb(flows ~ destination.pop+distance+origin-0, data=migration)
> sums3 <- aggregate(predict(model3,type='response'), by=list(migration$origin), sum)
> data.frame(origin=unique(migration$origin), observed=sums$x, poisson=sums1$x,quasi=sums2$x,negbin=sums3$x)
origin observed poisson quasi negbin
1 1 676308 676308 676308 651113.7
2 2...