similar to: too large dimension problem

Dear R family I have a following question. Suppose I have a matrix as follows, for instance: tau= 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 I want to calculate (-m) power of tau, for example, m=893. When I run tau^2, the outcome is just tau. Any help would be appreciated. thanks in advance. best moohwan

Dear R family I have a following question. Suppose I have a matrix as follows, for instance: tau= 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 I want to have the inverse of the above matrix and then add some exponent to it. That is, I want to calculate tau to the (-m). For example, m=893. Thanks in advance Best regards Moohwan Kim

Dear R family I am attempting to create a matrix. e.g., 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 How could I write a R program? Later I want to extend it to a N by N case. Thanks in advance best Moohwan

Dear R family, I have a question about how to detect some duplicate numeric observations. Suppose that I have two variables dataset. order value 1 0.52 2 0.23 3 0.43 4 0.21 5 0.32 6 0.32 7 0.32 8 0.32 9 0.32 10 0.12 11 0.46 12 0.09 13 0.32 14 0.25 ; Could you help me indicate where the duplicate observations in a row (e.g., 0.32) are? best, moohwan

Dear R family, I faced a technical problem in r coding. #s=t(dev)%*%dev/(nr-1) # dev (100,000 by 2) stands for deviation from the mean #sinv=solve(s) #t2=diag(dev%*%sinv%*%t(dev)) I got an error message at t2 statement: Error in diag(dev %*% si %*% t(dev)) : allocMatrix: too many elements specified Please let me know if there is a way to overcome this problem. best moohwan

Dear R family I have an arbitrary column vector. 1 2 4 0 7 5 0 0 0 9 11 12 When I attempt to take natural logarithm of the series, as you guess there is an error message. To overcome this problem, my idea is to replace a zero or zeros in a row with appropriate numbers. In order to implement it, I need to detect where zeros are. Then I am going to take the average of two adjacent neighbors. In the

Dear R family, Suppose I have two series. order value 1 0.52 2 0.23 3 0.43 4 0.21 5 0.32 6 0.32 7 0.32 8 0.32 9 0.32 10 0.12 11 0.46 12 0.09 13 0.32 14 0.25 For these two series, I figured out the way to detect the locations of duplicate values. The next thing to do is remove the repeated values except for a value that would not be next to each other. In other words, while keeping the

I want to generate the following outcome using convolution of two sequences. x <- c(1,2,3,4,5) y <- c(6,7,8,9) The resulting convolution vector is 6 19 40 70 100 94 76 45 When using convolve(), it is hard to produce the result above. Would you help me out to get that? Best regards Moohwan Kim

a=[0.1,0.2,0.1,0.3,0.4] b=[0.2,0.3,0.1,0.2,0.5] c=[1,1,1,1,1] log(c+a-x*b) where x=unknown scale variable. int=$$log(c+a-x*b)dadb, where $ denotes integral sign. Actually, how could I calculate the integral's approximation? double summation? best, moohwan

Hello, I would like to use mapply to avoid using a loop but for some reason, I can't seem to get it to work. I've included copies of my code below. The first set of code uses a loop (and it works fine), and the second set of code attempts to use mapply but I get a "subscript out of bounds" error. Any guidance would be greatly appreciated. Xj, Yj, and Wj are also lists, and s2,

Dear R users, I have the following codes: zeta <- rep(1,8) n <- 7 for (i in 1:2){ beta <- zeta[1:n+(i-1)*(n+1)] print(beta) parm <- zeta[i*(n+1)] print(parm) } ################### The output is as follows: [1] 1 1 1 1 1 1 1 [1] 1 [1] NA NA NA NA NA NA NA [1] NA ####################### The outcome I want to get is: [1] 1 1 1 1 1 1 1 [1] 1 [1] 1 1 1 1 1 1 1 [1] 1 How could I get the

Full_Name: Edward Huang Version: 2.6.1 OS: Mac OS 10.5.1 Leopard Submission from: (NULL) (71.198.106.232) I'm trying to run quantile regression on my data. I just couldn't make it work. The same dataset ran okay on STATA 10, tho. Would you please take a look at it? Here is the error message: *** caught segfault *** address 0x3ff00008, cause 'memory not mapped' Traceback:

Dear all, I am trying to compare the estimated coefficients of a quantile regression model between two different samples. It is a Wald test, but I cannot find one way to do that in R.The samples are collected conditional on a specific characteristic and I would like to test whether such characteristic indeed affect the estimators. The problem in the test anova.rq is that the response variable

Venables and Ripley describe a speedup where you take a structure like x<-NULL for(i in sequence) y<-c(y,function(x,i)) and convert it to one like x<-numeric(its length) for(i in sequence) y[i]<-function(x,i) I tried this speedup on some simple examples and it made them twice as fast. But now I am hitting a snag with some real code. This original version works:

Hello. I am a beginer in R and I can not implement the KhmaladzeTest in the following command. Please help me!!!!!!!!!!! PD: I attach thw results and the messages of the R program R : Copyright 2006, The R Foundation for Statistical Computing Version 2.3.1 (2006-06-01) ISBN 3-900051-07-0 R es un software libre y viene sin GARANTIA ALGUNA. Usted puede redistribuirlo bajo ciertas

Hi, I'd like to make a legend with a mix of mathematical symbol (tau), numeric variable and character variables.I have tried : types<-c("Type 1","Type 2","Type 2") tau<-c(1,3,2) legend(x="topright",legend=paste(types,"tau=",expression(tau))) but it doesn't work: the 'tau' symbol is not written in its 'symbol

Hi all, I would like to ask a question related to Kendall package. I ran Kendall (x,y) and saw the results. But I am not sure which tau values R reported. I have ties in my data set, so I want tau-b. Can anybody tell how Kendall package is calculating tau values? I have looked at the package PDF, but I could not find any useful information. As long as I see from the following link, there

Hello there Can anybody please tell me if there is any package in R to solve the following 4 nonlinear equations with 4 unknowns: alpha*exp(20/sigma)+ beta*exp(21/tau) = 2 alpha*exp(22/sigma)+ beta*exp(9/tau) = 4 alpha*exp(10/sigma)+ beta*exp(30/tau) = 6 alpha*exp(40/sigma)+ beta*exp(39/tau) = 5 where alpha = exp(lambda/sigma) beta= exp(delta/tau) I need to estimate lambda, sigma, delta, tau

Dear Rxperts, Running the following code: ======================================================= twlo=10; twhi=20; wt=154; vd=0.5; cl=0.046; tau=6; t=3; F=1; wtkg <- wt/2.2 # convert lbs to kg vd.pt <- wtkg * vd # compute weight-based vd (L) cl.pt <- wtkg * cl # compute CL (L/hr) k <- cl.pt/vd.pt # compute k (hr^-1) cave <-

Hi all, I am using quantile regression with svy design. I want to retrieve summary regression statistics (std error, p-value), since I don't have any in my output: Commands: clus1_d<- svydesign(id=~cd002_co, weights=~wtper, strata=~str, data=data) bclus1<-as.svrepdesign(clus1_d,type="bootstrap",replicates=100) fit1<-