search for: c_rnorm

Displaying 8 results from an estimated 8 matches for "c_rnorm".

2016 Jun 30
2
Calling C implementations of rnorm and friends
Hi all, Looking at the body for the function rnorm, I see that the body of the function is: .Call(C_rnorm, n, mean, sd) I want to implement functions that generate normal (and other) random variables. Now, I understand that I can perfectly well just call the R wrapper for these functions and that will be almost indistinguishable for most purposes, but for whatever reason I wanted to try and call the C...
2016 Jul 01
2
Calling C implementations of rnorm and friends
...erating functions, do you have any idea of where the source code is in the stats package? As I said above, I can't seem to find the source code for the functional forms. Thanks, Luis On Thu, Jun 30, 2016 at 10:38 PM, Gabriel Becker <gmbecker at ucdavis.edu> wrote: > Luis, > > C_rnorm is a symbol but it's not exported. This means that you *can* do > this by using stats:::C_rnorm. > > That said, it's not exported, which means that it's not supported to do > this. So your package likely would not be allowed on CRAN, for example. > > Best, > ~G &gt...
2016 Jun 30
0
Calling C implementations of rnorm and friends
Luis, C_rnorm is a symbol but it's not exported. This means that you *can* do this by using stats:::C_rnorm. That said, it's not exported, which means that it's not supported to do this. So your package likely would not be allowed on CRAN, for example. Best, ~G On Jun 30, 2016 2:08 PM, "Luis...
2016 Jul 01
1
Calling C implementations of rnorm and friends
.../271616 > > That should give you a few pointers on where/how to look. > > > Thanks, > > > > Luis > > > > On Thu, Jun 30, 2016 at 10:38 PM, Gabriel Becker <gmbecker at ucdavis.edu> > > wrote: > > > >> Luis, > >> > >> C_rnorm is a symbol but it's not exported. This means that you *can* do > >> this by using stats:::C_rnorm. > >> > >> That said, it's not exported, which means that it's not supported to do > >> this. So your package likely would not be allowed on CRAN, for...
2016 Jul 01
0
Calling C implementations of rnorm and friends
...age" from this answer: http://stackoverflow.com/a/19226817/271616 That should give you a few pointers on where/how to look. > Thanks, > > Luis > > On Thu, Jun 30, 2016 at 10:38 PM, Gabriel Becker <gmbecker at ucdavis.edu> > wrote: > >> Luis, >> >> C_rnorm is a symbol but it's not exported. This means that you *can* do >> this by using stats:::C_rnorm. >> >> That said, it's not exported, which means that it's not supported to do >> this. So your package likely would not be allowed on CRAN, for example. >> &g...
2017 Nov 22
2
function pointers?
...ops to 19.9 MB. That seemed like a lot of storage for a function's name. Why so much? My colleagues think the RAM use is high because this is a closure (hence closureList). I can't even convince myself it actually is a closure. The R source has rnorm <- function(n, mean=0, sd=1) .Call(C_rnorm, n, mean, sd) The storage holding 10000 copies of rnorm, but we really only need 1, which we can use in the objects. Thinking of this like C, I am looking to pass in a pointer to the function. I found my way to the idea of putting a function in an environment in order to pass it by reference:...
2002 Aug 05
1
constructing a formula
Dear Listers, I am having trouble figuring out how to build a formula using a variable list. For example, I have: a _ data.frame(a=rnorm(1000)) a$b_rnorm(1000)+.5*a$a a$c_rnorm(1000)+.5*a$b a$d_rnorm(1000)+.5*a$b+.1*a$a attach(a) and I estimate, lm(d ~ b+c+d) BUT, I wish to construct a generalized solution in which, ListOfVar _ c('b','c','d') The question is how to leverage ListOfVar into the constuction of the formula lm(a$d ~ a$b+a$c+a$b)....
2002 Jun 13
1
assign to data.frame
...works, but is slow and a "merge" is not really required. Rather a rbind will do the trick. However, there are a number of variables which need to be created in each data.frame to make the columns of the two data.frames similar. say, d1 <- data.frame(ind1=1:10,ind2=letters[1:10],c_rnorm(10)) d2 <- data.frame(ind1=21:30,ind2=letters[11:20],e_rnorm(10)) thus, d1 contains 'c' and d2 contains 'e' - with no overlap in ind1 and ind2. If I : d1$e <- rep(NA,10) d2$c <- rep(NA,10) I can, d <- rbind(d1,d2) # which is where I want to go. However, there are...