similar to: An "unsubsettable object" in a mixed model

Does your *shared* hosting account work without errors? I''m interested in both positive and negative reports. If you are willing, please contribute - name of the hosting service - how long you have used them - your experience ("flawless!", "it''s crap!") You *do not* need to reply saying your VPS service works great. This is about *shared* hosting

Dear R-users Has anybody implemented a function/package that will compute an individual's risk of an event in the presence of competing risks, adjusted for the individual's covariates? The only thing that seems to come close is the cuminc function from cmprsk package, but I would like to adjust for more than one covariate (it allows you to stratify by a single grouping vector). Any

1. There is, I believe, some redundant code in the calculation of the test statistic in ks.test in the package ctest. Lines 34-37 of the code read x <- y(sort(x), ...) - (0:(n - 1))/n STATISTIC <- switch(alternative, two.sided = max(abs(c(x, x - 1/n))), greater = max(c(x, x - 1/n)), less = -min(c(x, x - 1/n))) Lines 35-37 could read

Olly, I think the confdefs.h issue was due to the fact that I was using XAPIAN_CONFIG to point to the configure script, rather than the xapian_config executable created when making xapian_core, as pointed out by James. Also, as a general note, when trying to make the bindings, I had a problem when make was trying to compile the java source in org/xapian The following line: $(JAVAC)

Hi I have a dataframe which has 3 columns of numeric data A,B,C each of which has been obtained independent of the other. We are trying to find out, which of A or B cause C i.e. We are hypothesising that C is the effect and either A or B, not both is the cause. i.e. A causes C and this cause-effect relationship explains B. The data for A contains more noise than that for B. We are working with

Can't make sense of calculated results and hope I'll find help here. I've collected answers from about 600 persons concerning three variables. I hypothesise those three variables to be components (or indicators) of one latent factor. In order to reduce data (vars), I had the following idea: Calculate the factor underlying these three vars. Use the loadings and the original var

Hi, I have two dataframes: The first, df1, contains some missing data: cola colb colc cold cole 1 NA 5 9 NA 17 2 NA 6 NA 14 NA 3 3 NA 11 15 19 4 4 8 12 NA 20 The second, df2, contains the following: cola colb colc cold cole 1 1.4 0.8 0.02 1.6 0.6 I'm wanting all missing data in df1$cola to be replaced by the value of df2$cola.

dear list, I am wondering if one can find examples and/or more detailed descriptions of modifications needed when going beyond standard corStruct classes (i.e. those already provided for use in lme/nlme)? When I looked at pages 238-239 of Pinheiro/Bates (2000): Mixed-effects models in S and S-plus, I found that I would need a bit more explicit guidance what to do for implementing a new

Dear R users, I have a long function that among other things uses the "survest" function from the Design package. This function generates the warning: In survest.cph (...) S.E. and confidence intervals are approximate except at predictor means. Use cph(...,x=T,y=T) (and don't use linear.predictors=) for better estimates. I would like to turn this specific warning off, as it

Dear Friends, I am seeking for any help on an error message in lme functions. I use mixed model to analyze a data with compound symmetric correlation structure. But I get an error message: "Error in corMatrix.corCompSymm(object) : NA/NaN/Inf in foreign function call (arg 1)". If I change the correlation structure to corAR1, then no error. I have no clue how to solve this problem.

I am not in favor of the change, which is a choice of rigor over usability. When I am developing code or functions I agree with this, and I view any warnings from R CMD check about shortened arguments as positive feedback. But 90% of my usage of R is day to day data analysis, interactive, at the keyboard. A lot of data sets that come to me have long variable names. What this change will mean

I'm trying to learn how to do a repeated measures ANOVA in R using lme(). A data set that comes from the book Design and Analysis has the following structure: Measurements (DV) were taken on 8 subjects (SUB) with two experimental levels (GROUP) at four times (TRIAL). In SAS, I use the code: PROC MIXED DATA=[data set below]; CLASS sub group trial; MODEL dv = group trial group*trial;

Hello list: How to extract the value of "Rho" from a gnls() object. I am using gnls() function similar to res <- gnls(y~SSmicmen(),correlation=corCompSymm(form~1|b),data=dat) Thanks in advance, Mahbub. -- Mahbub Latif School of Mathematical Sciences Queen Mary, University of London United Kingdom [[alternative HTML version deleted]]

Dear R-users, I need to use the aftreg function in package 'eha' to estimate failure times for left truncated survival data. Apparently, survreg still cannot fit such models. Both functions should be fitting the accelerated failure time (Weibull) model. However, as G?ran Brostr?m points out in the help file for aftreg, the parameterisation is different giving rise to different

Hi all, How can I overcome the error "object of type 'closure' not subsettable" I ran the following script seq <- paste(seq(1914, 1916, by=1), "*.y", sep=".") # make sequence c <- 3 # total number of files d2 <- file # creates dummy file # Input sequence in loop for (i in 1:3){ list <- list.files("~/ukcp09/txt/x.djf", seq[[i]]) file

Hi everyone, Would somebody please explain (or point me to a reference that explains) the following error: "Error: object of type 'closure' is not subsettable" I was trying to use rep() to replicate a function: > example_function <- function() { return(TRUE) } > rep(example_function, 3) Error: object of type 'closure' is not subsettable But I just cannot

I'm attempting to write a general function to implement Faraway's bootstrapping algorithm for mixed models with lmer, but have run into a curious problem. I'm comparing two models model.1<-lmer(Response ~ Treatment + (1|Trial), data=exp.data, method="ML") model.2<-lmer(Response ~ 1 + (1|Trial), data=exp.data, method="ML") When I attempt to update

Hi All, I am trying to start R Server to run some Java Script in my local machine using the library, 'Rook'. I use Windows 7. And my codes are following, > library(Rook) > myD3dir <- 'D:\\STUDIES\\Java script\\d3-master' > s <- Rhttpd$new > s$start(quiet=TRUE) and i get the following error for the above line, Error in s$start : object of type

Hello folks: I have a data frame which includes two numeric vectors: "Pa1" and "Ingr" (which represents income).  I run the following code on the R console: ingreso <- factor(ifelse(Ingr<=3000,"bajo","alto")) tapply(Pa1,ingreso,summary) boxplot(Pa1~ingreso) and it works fine.  However, when I "Sweave" through an rnw file containing that

hey there! The object 'cit' contains: > cit ##################################################### # Johansen-Procedure Unit Root / Cointegration Test # ##################################################### The value of the test statistic is: 5.3484 9.0681 10.6433 --------------- I want R to save the value 5.3484 in a new object. I am used to use the command x=cit[a] where a