similar to: Using R-0.65.0 under ESS on Unix

Dear list: since it took me a little while to figure out how to make use of naresid, I thought that the below R code might be useful as an example on the help page. Regards, Markus # generate some data x1 <- runif(20) y <- 10 + 5*x1 + rnorm(20) summary(lm.0 <- lm(y ~ x1)) # append some NA's to y y <- c(y, rep(NA, 5)) # generate some further x1s x1 <- c(x1, runif(5)) #

Dear list: since it took me a little while to figure out how to make use of naresid, I thought that the below R code might be useful as an example on the help page. Regards, Markus # generate some data x1 <- runif(20) y <- 10 + 5*x1 + rnorm(20) summary(lm.0 <- lm(y ~ x1)) # append some NA's to y y <- c(y, rep(NA, 5)) # generate some further x1s x1 <- c(x1, runif(5)) #

I am having trouble using Jim Lindsey's libraries because of unresolved symbols. I am currently using R 0.65.0, but had this problem in earlier releases as well. I have a RedHat 6.0 Linux on i386 and use egcs (upgraded to that distributed with rawhide, after first failures with the libraries): egcs-g77-1.1.2-19 egcs-1.1.2-19 Installation of the libraries works but on loading >

Hi, maybe my question is not typical. I want to make R table-kind output to be readable immediately in Latex but I am struggling with symbol '\' needed for instance in '\hline'. For example when 'Table' is a matrix class object: cat("&",Table[1,1], "&",Table[1,2], "\n");flush.console() cat("\hline \n");flush.console()

Dear R-users, I intend to do a spatial analysis on the genetic structuring within a population. For this I had thought to prepare a kernel density estimate map showing the spatial distribution of individuals, while incorporating the genetic distances among individuals. I have a dataset of locations of N unique individuals (XY-coordinates) and an NxN matrix with the genetic distances given as a

This smells like a bug to me. The error is triggered by the line: variables <- eval(predvars, data, env) inside model.frame.default(). At that point, na.action has not been applied, so poly() ended being called on data that still contains missing values. The qr() that issued the error is for generating the orthogonal basis when evaluating poly(), not for fitting the linear model itself.

This smells like a bug to me. The error is triggered by the line: variables <- eval(predvars, data, env) inside model.frame.default(). At that point, na.action has not been applied, so poly() ended being called on data that still contains missing values. The qr() that issued the error is for generating the orthogonal basis when evaluating poly(), not for fitting the linear model itself.

Dear Debian R users, This is more of an apt question rather than R. I have a testing Debian system, but would like to use the unstable packages for R, *without* using the -t flag in apt-get. I think this is done by using a 'pin' rule in /etc/apt/apt.conf, but don't understand how this should be done. Can somebody provide an example please? Cheers, -- Seb

I would like to fit a Pareto Distribution and I am using the following codes. I thought the fitted (fit1) should be the fitted value for the data, is it correct? As the result of the "fitted" turns out to be a single value for all. fit=vglm(ycf1 ~ 1, pareto1(location=alpha), trace=TRUE, crit="c") fitted(fit) The result is fitted(fit) [,1] [1,] 0.07752694

Hello -- I am plotting multiple densities in a single plot. If the max of a new density (added with 'lines()') is sufficiently larger than that of the one first plotted (using 'plot()'), the new density is cut or trucated off of the figure. Is there a simple way of adjusting the yscale after all lines have been added? Or is the procedure to be used to first estimate all

Hi, I'm using the ineq package to calculate some concentration measures (Gini, Herfindal, ...) and I was wondering if there's around also a function to calculate standard error on these measures. If not, is anybody aware of where I can find a reference on this point? Thanks. -- ======================================================== Angelo Secchi PGP Key ID:EA280337

Dear helpeRs, I would like to specify a newline command in R and pass it to latex via Sweave such that it corresponds to latex' \\ command. But that doesn't seem to be possible. If I Sweave the \n character, it just makes a new line in latex but not the \\ command. Is there a way such that the following code would result in latex in blablabla \\ blablabla on different line

Dear all, I am using poly() in lm() in the following form. 1> DelsDPWOS.lm3 <- lm(DelsPDWOS[,1] ~ poly(DelsPDWOS[,4],3)) 2> DelsDPWOS.I.lm3 <- lm(DelsPDWOS[,1] ~ poly(I(DelsPDWOS[,4]),3)) 3> DelsDPWOS.2.lm3 <- lm(DelsPDWOS[,1]~DelsPDWOS[,4]+I(DelsPDWOS[,4]^2)+I(DelsPDWOS[,4]^3)) 1 and 2 lead to identical but wrong results. 3 is correct. Surprisingly (to me) the residuals

I have used library Design (Frank Harrell) in the past but when I tried this week, I get : > library(Design) Error in eval(expr, envir, enclos) : Object "formula.default" not found I updated to the latest version of the library (2.0) with the same result. My version of R may not be the latest but it's recent (and I probably changed since using Design for the last time) :

Dear All: I am having some trouble with date variables when NAs are present. The following example illustrates (see below for output of version): > library(chron) > minor.test <- c( "NA", "NA", "1988-02-08", + "1988-02-08", "NA", "1987-11-23", "1988-09-03", "1991-10-15", +

I am trying to calculate the weighted mean for a of 10 deciles and I get an error: > decile <- tapply(X=mat$trt1m, INDEX=mat$Rank, FUN=weighted.mean, w=mat$mcap) Error in FUN(X[[1]], ...) : 'x' and 'w' must have the same length All three of my inputs have the same length, as shown below, and the weighted.mean calculation works by itself, just not in tapply() >

Dear all; I'm planning to install Linux on my computer to run R (I'm bored of W..XP). However, I haven't used Linux before and I would appreciate, if possible, suggestions/comments about what could be the best option install, say Fedora, Ubuntu or OpenSuse which to my impression are the most popular ones (at least on the R-help lists). The computer is a PC desktop with 4GB RAM and

Hello R-users, I am using gls function in R to fit a model with certain correlation structure. The medol as: fit.a<-gls(y~1,data=test.data,correlation=corAR1(form=~1|aa),method="ML") mu<-summary(fit.a)$coefficient With the toy data I made to test, the estimate of mu is exactly equal to the overall mean of y which can not be true. But, if I make a toy data with y more than two

Hello: I am tried to install the RODBC package in debian etch. At the end of the installation it appears errors: ********************************************** * Installing *source* package 'RODBC' ... checking for gcc... gcc -std=gnu99 checking for C compiler default output file name... a.out checking whether the C compiler works... yes checking whether we are cross compiling... no

I am trying to use tapply to estimate the average wage in a set of Year*Education cells using sampling weights, as well as some other other statistics using the weights). I am having trouble trying to figure out how to pass the weights to the function, using: > tapply(wage,list(Educc,Year),weighted.mean, w=weight) whieh produces warnings of the type: 3: longer object length is not a