similar to: R-beta: Precedence of ~ and |

Hello, First a disclaimer :) I am very new to using R. I am generating some plots and eventhough I can get colored output in the encapsulated postscript files in the simplest of commands (e.g. plot(1:10,1:10, type="l", col="red") ), it does not work for the particular plots I want. It works on the screen. Here is an example taken out from "Mixed-Effects Models in S and

Tony Rossini sent me a copy of Jim's message to this list asking about nlme. I was surprised to find that I had not subscribed to this list. I thought I did but apparently not. I have now corrected that. Development of the nlme library (the name is from "nonlinear mixed-effects" but the library can also be used to fit general forms of linear mixed-effects models) is a continuing

Hi! Here is some output from an str command: > str(CO2) Classes ‘nfnGroupedData’, ‘nfGroupedData’, ‘groupedData’ and 'data.frame': 84 obs. of 5 variables: $ Plant : Ord.factor w/ 12 levels "Qn1"<"Qn2"<"Qn3"<..: 1 1 1 1 1 1 1 2 2 2 ... $ Type : Factor w/ 2 levels "Quebec","Mississippi": 1 1 1 1 1 1 1 1 1 1 ... $

Dear R-experts, I have a problem to formulate non linear mixed effects when more than one explanatory variable is present. I'm using R 1.1.1 under Linux. The version number of the nlme library is 3.1-7. "help(nlme)" says that among several possibilities it is possible to code fixed effects according to fixed = a1 + a2 + ... + an ~ X1 + X2 + ... + Xm where the left hand side

Given a data frame of a categorical variable and two continuous variables, I would like to display one continuous variable against the other for each value of the categorical variable, all superimposed on the same plot. For example: data(Indometh); str(Indometh) Classes 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 66 obs. of 3

Jose and I have a version of the lme (linear mixed effects) library that is known to work with at least one example on at least one version of R on at least one computer so that means it is time to upload to CRAN, right? In the near future a file lme_2.8-0.tar.gz will appear in the src/contrib/devel area under CRAN. Please remember this is a snapshot of the development version. We know there

Greetings, I have a groupedData (nmGroupedData) object created with the following syntax: Soil <- groupedData( ksat ~ conc | soil_id/sar/rep, data=soil.data, labels=list(x='Solution Concentration', y='Saturated Hydraulic Conductivity'), units=list(x='(cmol_c)', y='(cm/s)') ) the original data represents longitudinal observations in the form of:

I created the following groupedData object (nlme library): gd <- groupedData(Conc ~ Time | Subj, order.groups=T, FUN = myf, data=mydata) The idea of the myf function is to reverse the order of the grouping factor Subj (or better, reorder from largest to smallest). In the mydata data set, Subj is an integer that gets converted into a factor in the groupedData object. Does anyone

I am encountering difficulty with NextMethod in 0.50-a4. We created a class of groupedData objects which are data.frames with additional attributes. The most important attribute is a formula describing roles of some of the variables in the experimental design. The class of such objects ends in "groupedData", "data.frame". The print method for the groupedData class simply

Dear R-help, I am trying to create groupedData objects using the nlme library. I'm missing something basic, I know: Here is the first example in ch.1 of Pinheiro & Bates (2000): library(nlme) x2=Rail$travel;x1=Rail$Rail;eg1=data.frame(x1,x2);eg1gd=Rail print(eg1gd) x11();print(plot(eg1gd)) femodel=lm(x2~x1-1,data=eg1gd) print(femodel$coefficients) Result: x12 x15 x11

Hi everyone. I am trying to add a formula to my data using the groupedData function. My experiment consists of randomized block design using fruits, vegetation and time as factors. The idea is to see if fruits, vegetation and time explain the abundance of mice. I am using tree density as a covariate. So I tried to fit the following structure to my data. >

Hello, How do I specify the formula and random effects without a startup object ? I thought it would be a mixture of nls and lme. after trying very hard, I ask for help on using nlme. Can someone hint me to some examples? I constructed a try using the example from nls: #variables are density, conc and Run #all works fine with nls DNase1 <- subset(DNase, Run == 1 ) fm2DNase1 <- nls(

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

Dear all, I tried to create a groupedData object, where the grouping factor is not ordered. Here ist the code: library(nlme) test<-groupedData(conc~Time|Subject,order.groups=F,data=as.data.frame(Theoph)) > getGroups(test) Levels: 6 < 7 < 8 < 11 < 3 < 2 < 4 < 9 < 12 < 10 < 1 < 5 I still get an ordered factor. As always thanks for your help peter

Dea-R community. I'd like to draw your attention to an issue I have recently encountered while doing my current data analysis. I've got an unexpected (to me) result from the command: > augPred(lmList(my.object)), 'my.object' being a grouped data frame of class: > class(my.object) [1] "nfnGroupedData" "nfGroupedData" "groupedData"

# Your mailer is set to "none" (default on Windows), # hence we cannot send the bug report directly from R. # Please copy the bug report (after finishing it) to # your favorite email program and send it to # # r-bugs@r-project.org Reproducible Rterm crash. I drew a complicated graph, then resized the graphics window. R reported > Insufficient memory for resize. Killing device

I assigned a class the first problem in Pinheiro & Bates, which uses the data set PBIB from the SASmixed package. I have recently downloaded 2.0.1 and its associated packages. On trying library(SASmixed) data(PBIB) library(nlme) plot(PBIB) I get a warning message Warning message: replacing previous import: coef in: namespaceImportFrom(self, asNamespace(ns)) after library(nlme) and a

Dear listers, I am trying to fit a model using nlsList() using alternately a SSfol() selfstart function or its developped equivalent formulae. This preliminary trial works well mydata<-groupedData(Conc~Tps|Organ,data=mydata) mymod1<-nls(Conc~SSfol(Dose,Tps,lKe,lKa,lCl),data=mydata) as well as a developped form: mymod2<-nls(Conc~Dose * exp(lKe+lKa-lCl) *

I am having trouble fitting correlation structures within nlme. I would like to fit corCAR1, corGaus and corExp correlation structures to my data. I either get the error "step halving reduced below minimum in pnls step" or alternatively R crashes. My dataset is similar to the CO2 example in the nlme package. The one major difference is that in my case the 'conc' steps are

I am trying to create a plot similar to Figure 3.2 in Bates and Pinheiro. I have repeated measurements on about 80 subjects from 2 treatment groups. I would like to have the panels for the two treatment groups in separate groups and within those groups have the panels ordered on maximum value (as is the default). I am ok with getting plots similar to Figs 3.1 and 3.2, but can't see how to