similar to: Arguments to lm() within a function - object not found

Hi, I have some code that looks like: dftc <- df[sets$tcset,] pt <- numeric(nrow(dftc)) sub <- 1:nrow(dftc) for (i in 1:nrow(dftc)) { n <- nnet( fmla, data=dftc, weights=wts, subset=sub[-i], size=4, decay=0.01) pt[i] <- predict( n, dftc[ i, ], type='class' ) } However running this give me the error: Error in eval(expr, envir, enclos) :

I'm still getting used to R's scoping. I've run into the following situation value=0 thefunction <- function() print( value ) somefunction <- function() { value=99; thefunction() } somefunction() now, I understand that somefunction() returns 0 because thefunction() was defined with value=0 in its parent envrionment, it dosent look at all in the environment of somefunction. My

Hi, I am having trouble with the survival library, particualrily the coxph function. the following works coxph(jtree9$cph.call,z,rep(1,dim(z)[1])) Call: coxph(formula = jtree9$cph.call, data = z, weights = rep(1, dim(z)[1])) coef exp(coef) se(coef) z p SM 0.2574 1.294 0.0786 3.274 1.1e-03 Sex -0.1283 0.880 0.1809 -0.709

Hello, I've been working with "nnet" and now I'd like to use the weigths, from the fitted model, to iterpret some of variables impornatce. I used the following command: mts <- nnet(y=Y,x=X,size =4, rang = 0.1, decay = 5e-4, maxit = 5000,linout=TRUE) X is (m x n) Y is (m x 1) And then I get the coeficients by: Wts<-coef(mts) b->h1 i1->h1

Hi, I am doing double for loops to calculate SDs with some weights and wondering if I can get rid of the outer for loop as well. I made a simple examples which is essentially what I am doing. Thanks for your help! -Young #------------------------------------------------------ # wtd.var is Hmisc package # you can replace the 3 lines inside for loop as # sdx[i,] =

I was cursing Matlab again today (what else is new) because the default action for every Matlab command is to spew the result to the console, and one must remember to put that darn ";" at the end of every line. So I just wondered: was there ever a discussion as to providing some modified version of the "<-" and "->" operators in R to do the reverse?

Hi everybody. I have been searching and trying for an answer, but no luck, so here I go.. Is there anyway to execute multiple commands on a single priority in extensions.conf? eg: exten => X.,1,Dial(SIP/1111) & somefunction(${EXTEN}) I need the dial command to dial internal extensions, and the "somefunction" to kick of our own outgoing system for redirection to outside lines;

I could use some help understanding how nls parses the formula argument to a model.frame and estimates the model. I am trying to utilize the functionality of the nls formula argument to modify garchFit() to handle other variables in the mean equation besides just an arma(u,v) specification. My nonlinear model is y<-nls(t~a*sin(w*2*pi/365*id+p)+b*id+int,data=t1,

Dear R-users, I'm trying to work out a way to set default values for arguments in a function which includes the optional argument '...'. In practice, I have a 'plot' method for a function which specifies different types of plots. Every different plot should have different default arguments (for example for 'col', 'ylim' etc), plus the argument '...' to

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

Hello, outer() is great for avoiding things like: for (val1 in val1s) { for (val2 in val2s)) { x[i,j] <- somefunction(val1, val2) } } The same can be obtained with: outer(val1s, val2s, somefunction) But what if there are three (or more) sets of values to loop over? Any way of avoiding the loops then? Thanks, -- Wolfgang Viechtbauer

Hi all, I am trying to use llvm-gcc to link shared libraries on windows/mingw32. When I try to link libraries that contain functions declared with __declspec(dllexport) someFunction(); I get the link error: Cannot export _someFunction: symbol not found Removing the declspec directive solves the problem, but this is not a very feasible solution for me. Using 'regular' gcc does not

All: I am new to R and would like your help in identifying the appropriate process to follow in order to modify the output from an existing package. I've had difficulty finding an answer online, perhaps because I am using incorrect terminology. A package that I am using (mmlcr) invokes another package (multinom). An output of multinom is the standard errors, but this output is not

> I am trying to use llvm-gcc to link shared libraries on windows/mingw32. > When I try to link libraries that contain functions declared with >  __declspec(dllexport) someFunction(); > > I get the link error: > >  Cannot export _someFunction: symbol not found dllexport declspec should be put on the function definition, in this example there is nothing to export - dllexport

Hi all, I am going to be teaching a workshop next week using R and Bioconductor in one of our university's computer labs. They have recently installed R 2.4.1 for me, and I'm checking all my scripts. I just noticed that using the ?somefunction call to access the documentation for that function is not working. On my own PC, the ? call output changed between R 2.3 and 2.4; before it would

Hi all: This question is related to a state machine generated by LLVM for a coroutine. I stripped all coroutine related details to get to the essence of the question. Let's say I have a state machine that looks like this: struct State { FnPtr Fn; State() : Fn(&SomeFunction) {} void Go() { (*Fn)(); } void Stop() { Fn = nullptr; } bool IsDone() { return Fn ==

Hello I was trying to estimate the weibull model using nls after putting OLS values as the initial inputs to NLS. I tried multiple times but still i m getting the same error of Error in nlsModel(formula, mf, start, wts) : singular gradient matrix at initial parameter estimates. The Program is as below > vel <- c(1,2,3,4,5,6,7,8,9,10,11,12,13,14) > df <- data.frame(conc, vel) >

R-users E-mail: r-help@r-project.org I have a quenstion on "gam()" in "gam" package. The help of gam() says: 'gam' uses the _backfitting algorithm_ to combine different smoothing or fitting methods. On the other hand, lm.wfit(), which is a routine of gam.fit() contains: z <- .Fortran("dqrls", qr = x * wts, n = n, p = p, y = y *

I've run into a scoping problem in R. I'm calling a function that * creates a formula * calculates a weight vector * calls lm with that formula and weights This fails. Here's a simplified reproduce example: # f works, g doesn't, h is a workaround rm(w) data <- data.frame(y=runif(20), x=runif(20), z=runif(20)) f <- function(k){ w <- data$z^k coef(lm(y~x, data

Hi all Is there a function that can find the start and end position of peaks in a set of numbers. eg. x=c(14,15,12,11,12,13,14,15,16,15,14,13,12,11,14,12) y=somefunction(x) y 4 14 Thanks John [[alternative HTML version deleted]]