similar to: constructing a formula

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

Gabriel, Thanks for that! I guess I really should have figured that one out sooner, huh? I understand why that wouldn't be CRAN-compliant. But then, what *is* the proper way to do it? Is there any way I can call unexported functions from another package and have it accepted by CRAN? Also, if I instead re-write the random variable generating functions, do you have any idea of where the

Well, For this particular use case why not just transform the parameters at the R level and then call the existing function? Is there not a closed form mapping? ~G On Jul 1, 2016 2:50 PM, "Joshua Ulrich" <josh.m.ulrich at gmail.com> wrote: > On Fri, Jul 1, 2016 at 6:13 AM, Luis Usier > <luis.henrique.usier at gmail.com> wrote: > > Gabriel, > > > >

We have a project that calls for the creation of a list of many distribution objects. Distributions can be of various types, with various parameters, but we ran into some problems. I started testing on a simple list of rnorm-based objects. I was a little surprised at the RAM storage requirements, here's an example: N <- 10000 closureList <- vector("list", N) nsize = sample(x

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 Usier" <luis.henrique.usier at gmail.com> wrote: > Hi all, > >

On Fri, Jul 1, 2016 at 6:13 AM, Luis Usier <luis.henrique.usier at gmail.com> wrote: > Gabriel, > > Thanks for that! I guess I really should have figured that one out sooner, > huh? > > I understand why that wouldn't be CRAN-compliant. But then, what *is* the > proper way to do it? Is there any way I can call unexported functions from > another package and have it

Hello All! I''m novice at ROR. Would you like to explain what mean such constuction in Ruby. 1: class DemoController < ActionController::Base 2: scaffold :item 3: end Is 2th line calling of method ''scaffold''? If it is so, when it called? For all instances of class, or only for class? I watch sources of ActionController, but don''t understand completely.

Hi, First, thanks to those who helped me see my gross misunderstanding of randomForest. I worked through a baging tutorial and now understand the "many tree" approach. However, it is not what I want to do! My bagged errors are accpetable but I need to use the actual tree and need a single tree application. I am using rpart for a classification tree but am interested in a more unbaised

I have two large data.frames which I would like to combine. Merge 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 <-

Hi Yawl, After about 6 months of prattting about I've convinced my boss that we should be installing * into our currently under constuction Data Center in Somerset NJ. There will be 10 permanent people and DR space for another 50. My plan is as follows; ATAComm dual XEON server with quad T1 board. A handfull of ATA's for fax machines, job lot of X-Pro softphones for the DR bit, Polycom

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Trying to work out a model formula that will do what I want ... suppose I want to model y = b_i x + epsilon (i.e. a linear model with zero intercept and with slopes differing by groups), and I want to parameterize the slopes in the "usual" way of having a baseline slope value for the first level of the factor b and (n-1) values

I'm working on some functions for generalized canonical discriminant analysis in conjunction with the heplots package. I've written a candisc.mlm function that takes an mlm object and computes a candisc object containing canonical scores, coeficients, etc. But I'm stumped on how to construct a mlm for the canonical scores, in a function using the *same* right-hand-side of the model

Sorry to be posting another question, but my learning curve is starting to flatten some now. What am I missing here? > temp _ name[reis==toupper(location[order(Vgrablow2)][N])] > temp [1] "Lawton" > paste(temp,g) [1] "Lawton" # WHERE IS THE SECOND ELEMENT? > g [1] 0.29 > a _ "Lawton" > paste(a,g) [1] "Lawton 0.29"

I need to construct all possible combinations of an vector of length N taken X at a time for simulation purposes. Taking a a small vector as an example: >input <- c('a','b','c','d') >somefunction(input) a,b,c a,b,d a,c,d b,c,d my only solution thus far is: somefunction <- function(x){ ...a series of grotesque and horribly inefficient loops

I have a question regarding application of model coefficients between datasets. In particular, I have several datasets which I would like to apply a model estimated from only a single dataset (sort of a crude - out of sample application - to show the variances). lets say, names(a) [1] "stdnoi" "momentum" "tbm3" "metcons" "premium"

I am just starting to learn Sweave (really neat tool). I am pretty early in the learning curve (I had to think a moment ago whether a # or % was the appropriate comment character). I have successfully incorporated simple graphics and outputs, but am having trouble getting a latex (xtable) table to function properly. Latex is seemingly treating the xtable code as input or verbatim text. That

I have a, no doubt, simple question. I wish to write a function such that a <- 9 b <- 10 changer _ function(x,y) { if (y>x){ x <<- Y+1}} Of course there are easier ways to accomplish the task above, but I am more interested in how to have the "x <<- Y+1" part of the function to change x in place for purposes of a much larger function. I have been wrestling with

hello, this is my script: #1) read in data: daten<-read.table('K:/Analysen/STRUCTURE/input_STRUCTURE_tab_excl_5_282_559.txt', header=TRUE, sep="\t") daten<-as.matrix(daten) #2) create empty matrix: indxind<-matrix(nrow=617, ncol=617) indxind[1:20,1:19] #3) compare cells to each other, score: for (s in 3:34) { #walks though the matrix colum by colum, starting at

I am trying to pass an equation as an arguement to a function, which seems pretty straightforward given lazy evaluation. I constructed the following little test to make sure I sort of knew what I was doing: go <- function(X,eq) { C <<- X*2; d <<- eq} a _ rnorm(100) go(10,eq=a[.5*length(a)]+C+1) > C [1] 20 > d [1] 21.10551 > a[.5*length(a)] [1] 0.1055086 Everything

Hi, Apart from checking each field in an object created from form params, is there an easy way I can construct a query from an object? For example, I''m doing this: @candidate = Candidate.new(params[:candidate]) And go on to check each attribute if it''s blank and thereby constructing a query. It''s pretty common, so I''m guessing there should be a easier