search for: nsims

Dear all, I have just sent an email with my problem, but I think no one can see the red part, beacuse it is black. So, i am writing again the codes: rm(list=ls()) #remove almost everything in the memory set.seed(180185) nsim <- 10 mresultx <- matrix(-99, nrow=1000, ncol=nsim) mresultb <- matrix(-99, nrow=1000, ncol=nsim) N <- 200 I <- 5 taus <- c(0.480:0.520) h <-

Dear all, I am a new user in r and I am facing some problems with the quantile regression specification. I have two matrix (mresultb and mresultx) with nrow=1000 and ncol=nsim, where I specify (let's say) nsim=10. Hence, the columns in my matrix represents each simulation of a determined variable. I need to regress each column of mresultb on mresultx. My codes are the following:

Dear all, I am trying to run a loop in my codes, but the software returns an error: "subscript out of bounds" I dont understand exactly why this is happenning. My codes are the following: rm(list=ls()) #remove almost everything in the memory set.seed(180185) nsim <- 10 mresultx <- matrix(-99, nrow=1000, ncol=nsim) mresultb <- matrix(-99, nrow=1000, ncol=nsim) N

Running the function below, tested using the cardiff dataset from splancs generates the following error. What changes do I need to make to get the function to work? Thanks. --Dale > gen.rpoints(events, poly, 99) > rpoints Error: object "rpoints" not found # test spatial data library(splancs) data(cardiff) attach(cardiff) str(cardiff) events <- as.points(x,y) ###

This is my current work.Now i am trying to use a function to do the normal distribution simulation. rm(list=ls()) t <- u<- mann<- rep(0, 45) Nsimulation<-function(S1,S2,Sds,nSims) { set.seed(1) for (sim in 1:nSims) { matrix_t <-matrix(0,nrow=nSims,ncol=3) matrix_u<-matrix(0,nrow=nSims,ncol=3) matrix_mann <-matrix(0,nrow=nSims,ncol=3) #generate random samples from 2 normal d...

I?m working on an R-implementation of the simulation-based finite-sample null-distribution of (R)LR-Test in Mixed Models (i.e. testing for Var(RandomEffect)=0) derived by C. M. Crainiceanu and D. Ruppert. I'm in the beginning stages of this project and while comparing quick and dirty grid-search-methods and more exact optim()/optimize()-based methods to find the maximum of a part of the

...written 11 codes separately for all of the cases. But i have been told that it can all been done within one code. can anyone give me a brief idea on it. I just managed to write till here and it perhaps isnt correct .. #set up matrix for storing data from simulation matrix_t <-matrix(0,nrow=nSims,ncol=3) matrix_u<-matrix(0,nrow=nSims,ncol=3) matrix_mann <-matrix(0,nrow=nSims,ncol=3) sample_sizes<- matrix(c(10,10,10,25,25,25,25,50,25,100,50,25,50,100,100,25,100,100), nrow=2) p1<-p2<-p3<-vector() nSims<-10 alpha<-0.05 set.seed(1)...

...use R 1.8.0 and Windows XP professional. My computer has a Pentium 4 2.4 with 512 MB memory. Thanks in advance. best regards, Yu-Kang Tu Clinical Research Fellow Leeds Dental Institute University of Leeds ## change scores simulation close.screen(all=TRUE) split.screen(c(3,3)) nitns<-10000 nsims<-100 r<-0.1 param1<-c(1:nitns) param2<-c(1:nitns) param3<-c(1:nitns) param4<-c(1:nitns) param5<-c(1:nitns) param6<-c(1:nitns) param7<-c(1:nitns) param8<-c(1:nitns) param9<-c(1:nitns) param10<-c(1:nitns) param11<-c(1:nitns) param12<-c(1:nitns) param13<-c(...

## Package Needed library(fields) ## Assumptions set.seed(123) nsim<-5 p<-2 ## Generate Random Matrix G G <- matrix(runif(p*nsim),nsim,p) ## Set Empty Matraces dmax and dmin dmax<- matrix(data=NA,nrow=nsim,ncol=p) dmin<- matrix(data=NA,nrow=nsim,ncol=p) ## Loop to Fill dmax and dmin for(i in 1:nsim) { dmax[i]<- max(rdist(G[i,,drop=FALSE],G)) dmin[i]<-

...to matrix then use a loop for sample sizes sample_sizes<- matrix(c(10,10,10,25,25,25,25,50,25,100,50,25,50,100,100,25,100,100), nrow=2) #create vector to combine all std deviations sds<-c(4,6,8,10,12,14) # this number is needed below nsds<-length(sds) set.seed(8) #number of simulations nSims<-10000 #set significance level,alpha for the whole simulatio alpha<-0.05 #set empty vector of length no.of _calculations_ to store p-values # Note: you have 54 calculations, not 10000 ncalcs<-dim(sample_sizes)[2]*nsds t_equal <-c(rep(0,length=ncalcs)) t_unequal <-c(rep(0,length=ncal...

Dear all, Does anyone have any idea on how to speed up the for() loop below. Currently it takes approximately 2 minutes and 30 seconds. Because of the size of Nsim and N, simulating a multivariate normal (instead of simulating Nsim times a vector of N normal distributions) would require too much memory space. Many thanks for your kind help, Simona N=3000 PD=runif(N,0,1) cutoff.=qnorm(PD)

I am running 1.3.1 on a Windows (NT 4.0) machine. I've fit a nonlinear model intended to predict crop yield from nutrient information, and want to use the profile function. If I type say, profile(simparj.fm) I get the following error message: "Error in prof$getProfile(): number of iterations exceeded maximum of 5.25515e-308" I used the profiler function to profile simparj,fm step

...es<- > matrix(c(10,10,10,25,25,25,25,50,25,100,50,25,50,100,100,25,100,100), > nrow=2) > > #create vector to combine all std deviations > sds<-c(4,6,8,10,12,14) > # this number is needed below > nsds<-length(sds) > set.seed(8) > > #number of simulations > nSims<-10000 > #set significance level,alpha for the whole simulatio > alpha<-0.05 > > #set empty vector of length no.of _calculations_ to store p-values > # Note: you have 54 calculations, not 10000 > ncalcs<-dim(sample_sizes)[2]*nsds > t_equal <-c(rep(0,length=ncalcs))...

Craig, Thanks for your follow-up note on using the asypow package. My problem was not only constructing the "constraints" vector but, for my particular situation (Poisson regression, two groups, sample sizes of (1081,3180), I get very different results using asypow package compared to my other (home grown) approaches. library(asypow) pois.mean<-c(0.0065,0.0003) info.pois <-

Dear list, After running for a while, it crashes and gives the following error message: can anybody suggest how to deal with this? Error in if (ratio0[i] < log(runif(1))) { : missing value where TRUE/FALSE needed ################### original program ######## p2 <- function (Nsim=1000){ x<- c(0.301,0,-0.301,-0.602,-0.903,-1.208, -1.309,-1.807,-2.108,-2.71) # logdose

Hi R-users, I have a problem for updating the estimates of correlation coefficient in simulation loop. I want to get the matrix of correlation coefficients (matrix, name: est) from geese by using loop(500 times) . I used following code to update, nsim<-500 est<-matrix(ncol=2, nrow=nsim) for(i in 1:nsim){ fit <- geese(x ~ trt, id=subject, data=data_gee, family=binomial,

I normally use the following code to create a figure displaying the mark correlation function for the point pattern process "A": M<-markcorr(A) plot(M) I have now started to use the following code to perform 1000 Monte Carlo simulations of Complete Spatial Randomness (CSR). It is a Monte Carlo test based on envelopes of the Mark correlation function obtained from simulated point

I've written the function below to simulate the mean 1st through nth nearest neighbor distances for a random spatial pattern using the functions nndist() and runifpoint() from spatsat. It works, but runs relatively slowly - would appreciate suggestions on how to speed up this function. Thanks. --Dale library(spatstat) sim.nth.mdist <- function(nth,nsim) { D <- matrix(ncol=nth,

Hello! I have a matrix with data and a column indicating whether it is censored or not. Is there a way to apply weibull and exponential maximum likelihood estimation directly on the censored data, like in the paper: Backtesting Value-at-Risk: A Duration-Based Approach, P Chrisoffersen and D Pelletier (October 2003) page 8? The problem is that if I type out the code as below the likelihood

Hi all, I would like to estimate power and necessary sample size for a GLM with a response variable that has a poisson distribution. Do you have any suggestions for how I can do this in R? Thank you for your help. Sincerely, Craig -- Craig A. Faulhaber Department of Forest, Range, and Wildlife Sciences Utah State University 5230 Old Main Hill Logan, UT 84322 (435)797-3892