similar to: Predicting a single observatio using LME

Once again I need to tap into the collective knowledge here. Let's say I have the following columns and data below Y X1 X2 X3 X4 I would like to generate additional new columns and column names (ie the data would be squared - and I'd like the column names to reflect this) like: Y X1 X2 X3 X4 X1^2 X2^2 X3^2 X4^2 I believe I can compute the values correctly with the code below, but I

Hello Everyone, I have what I think is a complex text parsing task. I've provided some sample data below. There's a relatively simple version of the coding that needs to be done and a more complex version. If someone could help me out with either version, I'd greatly appreciate it. Here are my sample data. haveData <- structure(list(profile_key = structure(c(1L, 1L, 2L, 2L, 2L,

The print method for lme *prints out* the fitted correlation matrix for the random effects. Is there any way to get these values as an object in R? I have examined the components of the lme object (called "junk" in the example below) and the components of summary(junk) without finding these numbers. (How I did this: I dumped the entire lme object to a text file and then used egrep to

Hi all, I tried to do a variance components using nlme, but I got the following warning mesage ##################################################### not meaningful for factors in: Ops.factor(y[revOrder], Fitted) ###################################################### Can someone point out what is the meaning of this warning message? I tried to look at Ops.factor, but I don't

I'm attempting to run an LME model with random intercepts for location and have received an error message. The model and error message are given below: > mixed.distance <- lme (fixed= log(min5inpnc) ~ i93centerline, random=~1|location, data = nosmokecomp) Error in y[revOrder] - Fitted : non-conformable arrays I believe that my dataset may have dimensions that are not working with

dear R wizards: X is factor with 20,000*20=800,000 observations of 20,000 factors. I.e., each factor has 20 observations. y is 800,000 normally distributed data points. I want to see how much R^2 the X factors can provide. Easy, right? > lm ( y ~ X) and > aov( y ~ X) Error: cannot allocate vector of size 3125000 Kb is this computationally infeasible? (I am not an expert, but

Hello, How would you go about handling the following situation? This is on R 2.12.0 on Ubuntu 32-bit. I have a wrapper function to lm. I want to pass in a subset argument. First, I just thought I'd use "...". ## make example reproducible set.seed(123) df1 <- data.frame(age = rnorm(100, 50, 10), bmi = rnorm(100, 30, sd = 2)) ## create a wrapper using

Sorry if this is obvious, but my S skills aren't great and I haven't been able to find it documented anywhere. I want to write a new function for use with lme objects; the function will simply calculate an ICC (aka "rho") for each level of a mixed-effects model. What I need for this is pretty simple: (c(var1..varn, residual)) / sum(c(var1..varn, residual)) where var1..varn

Hello everyone! I would really appreciate it if someone knew where could I find the command in R in order to run a fixed effects regression. What format should my data have? I have looked through the manual and I could not find anything Thank you in advance, Petros [[alternative HTML version deleted]]

I want to take the first row of each unique ID value from a data frame. For instance > ddTable <- data.frame(Id=c(1,1,2,2),name=c("Paul","Joe","Bob","Larry")) I want a dataset that is Id Name 1 Paul 2 Bob > unique(ddTable) Will give me all 4 rows, and > unique(ddTable$Id) Will give me c(1,2), but not accompanied by the name column.

Hello all. I was wondering if the logLike.nls() and logLike.nlme() functions are still being used. Neither function seems to be available in the most recent release of R (1.9.1). The following is contained in the help file for logLik(): "classes which already have methods for this function include: 'glm', 'lm', 'nls' and 'gls', 'lme' and others in

In an attempt to learn to use the rv package, I have been working through the examples in Jouni Kerman and Andrew Gelman's "Using Random Variables to Manipulate and Summarize Simulations in R" (July 4, 2007). I am using a Dell Precision 380n computer running Gentoo Linux and R 2.2.1 (the latest available through Gentoo's portage/emerge system). Everything worked well until I

Greetings R-helpers, I am attempting to fit an lme() while specifying a correlation structure, but I'm getting into trouble long before I get to that point. I am receiving the error: Error in y[revOrder] - Fitted : non-conformable arrays It doesn't seem to matter how simple or complex the model I specify is, it always gives this same error message. This makes me suspect something is

I am writing a program in which I would like to take in a formula, change the response (Y) variable into something else, and then pass the formula, with the new Y variable to another function. That is, I am starting with formula <- Y~X1+X2+X3 and I'd like to do something like Y <- formula$Y newY <- f(Y) lm(newY~X1+X2+X3) So far, it seems that my

Hello everybody. I am trying to upgrade from R-1.9.0 to R-1.9.1 on a RedHat linux 2.4.18 system. I get the following error after "tar -xvzf R-1.9.1.tgz ; cd ./R-1.9.1/ ; ./configure" and "make" : [make works for 10 minutes ... snip ...] varExp text html latex varFixed text html latex varFunc

Hello all, When I ran my R program in R version 2.1.1 in windows XP and 2000, and I downloaded a package call "MIX", I got an application error: RGui:Rgui.exe - Application Error: The instruction at "0x1009d8a1" referenced memory at "0xbde48f58". The memory could not be "read". Click on ok to terminate the program click on cancel to debug the program

I am trying to estimate models with subsets using the NLME package. However, I am getting an error in the case below (among others): > subset <- c(rep(TRUE, 107), FALSE) > fm2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1, subset=subset) Error in xj[i] : invalid subscript type 'closure' > fm2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1,

I am in the process of submitting a package to CRAN. R CMD check ran successfully on the package on my local computer, using R version 2.1.1. However, on the computers for CRAN (with version 2.10.0), the following errors occurred: Warning in parse_Rd("./man/predict.Rd", encoding = "unknown") : ./man/predict.Rd:28: unknown macro '\dquote' *** error on file

How is exact pattern matching achieved in GREP (and GREPlike) functions ? # Want: listing of all object names that end in *.lm > objects(pattern="*.lm",pos=1) # ... but get: all objects that partially match *.lm, e.g., *.lme [1] "j3.lm" "J3.lme" "j8.lm" "J8.lme" # Want: position of string "4jan2002" in vector >

I am creating an R package. I ran R CMD check on the package, and everything passed until it tried to run the examples. Then, the result was: * checking examples ... ERROR Running examples in REEMtree-Ex.R failed. The error most likely occurred in: > ### * AutoCorrelationLRtest > > flush(stderr()); flush(stdout()) > > ### Name: AutoCorrelationLRtest > ### Title: Test for