similar to: Contrasts in lm

In the 'doBy' package there is an esticon() function for calculating linear contrasts for various model types. I have defined an S3-method 'esticon.mer()' for 'mer' objects from the lme4 package. Building the package and invoking the method gives: > esticon(fm1, c(1,1)) Confidence interval ( WALD ) level = 0.95 Error in as.integer(x) : cannot coerce type 'S4'

Dear all, In S+, there are functions like create.ole.object call.ole.method release.ole.object for communicating with other programs which work as a COM server (on Windows). Is it possible to do something similar in R (I've studied the 'connections' facilities, but they do not seem to work). ========================================== S?ren H?jsgaard, PhD, Senior Scientist

I have a .txt file obtained by saving a data frame in which the first four columns are factors (but represented as 1,2,3 etc). The first four lines are "Pig" "Evit" "Cu" "Litter" "Start" "Weight" "Feed" "Time" "4601" "1" "1" "1" 26.5 26.5 NA 1 "4601" "1"

As a sequel to my previous mail on cut, formatC does not produce what I have been taught is significant digits: > x <- c(1.0793,1.0796, 11.0954, 11.0736 ) > formatC(x,digits=3,format="g") [1] "1.08" "1.08" "11.1" "11.1" (3,3,3,3) significant digits OK > formatC(x,digits=3,format="f") [1] "1.079"

Hi, SAS transport files created with the xport engine in SAS can be read using read.xport. However, the xport engine only works with SAS version 6, and consequently long variable names are not allowed... Can anyone tell me how to get SAS data (ver 8) into R (easily)? Thanks in advance S?ren H?jsgaard sorenh at agrsci.dk http://www.jbs.agrsci.dk/~sorenh

Further to the discussion between Murray Jorgensen and Brian Ripley, it seems to me better to choose tabulations that will not come and bite you. Suppose your data are sligtly irregular, e.g. (for the sake of the argument): data( warpbreaks ) warpbreaks$variant <- rep( 1:5, len=54 ) attach( warpbreaks ) tb <- table( wool, tension, variant ) tb # in this case you would like to see: tp

Further to the discussion between Murray Jorgensen and Brian Ripley, it seems to me better to choose tabulations that will not come and bite you. Suppose your data are sligtly irregular, e.g. (for the sake of the argument): data( warpbreaks ) warpbreaks$variant <- rep( 1:5, len=54 ) attach( warpbreaks ) tb <- table( wool, tension, variant ) tb # in this case you would like to see: tp

For doumentation purposes I run a batch R program that does reshaping etc. of data and finally prints things. When I paste the code into an R-window everything runs in a few seconds, but in Batch mode i get in the output file the result below. Any clues why R uses 4 min to print a 1129\times 6 dataframe in batch mode? The scrit I use to run R is: c:\stat\r\%R_VERS%\bin\Rterm --no-restore

Hi, I've data from an incomplete fatorial design. One level of a factor doesn't has the levels of the other. When I use lm(), the summary() return NA for that non estimable parameters. Ok, I understant it. But I use contrast::contrast(), gmodels::estimable(), multcomp::glht() and all these fail when model has NA estimates. This is becouse vcov() and coef() has different dimensions. Is

Hello all Can R be used as a COM client (rather than as a COM server)? The following (Splus) code shows the sort of thing I'd like to do: pMIM <- create.ole.object("mim31.Server") NoOutputLines <- call.ole.method(pMIM, "SendCmdLine", "show w") for (i in 1:NoOutputLines) show(call.ole.method(pMIM, "GetOutputLine")) release.ole.object(pMIM)

I run Win2000, and when I try to write to a file and later use it it seems that R 1.02.0 has a firm grip on it: > version _ platform i386-pc-mingw32 arch x86 os Win32 system x86, Win32 status major 1 minor 2.0 year 2000 month 12 day 15

I am using the following model: lm <- lm(mydata[[variableName]] ~ Age + Gender + Group, data=mydata) There are 5 groups in "Group": nonc (the control), c1,c2,c3 and c4. How do I contrast nonc vs the others? and How do I contrast c1 vs other c's (ie c2,c3,c4 as a subgroup)? I have looked at the contrasts option in lm and model.matrix and am really none the wiser. Though it

Hi, I would like apply different link functions from Aranda-Ordaz (1981) family to large binary dataset (n = 2000). The existing links in glm for binomial data (logit, probit, cloglog) are not adequate for my data, and I need to test some other transformations. Is it possible to do this in R? And how? Thank you for your help, /Sharon

Dear all, I have used the Scompile package (by Mathhew Calder) on previous releases of R (on Windows), and it has worked well. However, R.1.3.1 crashes when dyn.load'ing C-functions created by Scompile. >From the last R-newsletter it seems that there has been some changes to how external routines are being included in version 1.3.1. I won't claim to understand the details, but I was

I did some serach around. It seems that ROC curve computation is not supported on R. Anyone has some leads? Thanks. Jason ===== Jason G. Liao, Ph.D. Division of Biometrics UMDNJ School of Public Health 335 George Street, Suite 2200 New Brunswick, NJ 08903-2688 phone (732) 235-9748, fax (732) 235-9777 http://www.geocities.com/jg_liao __________________________________________________ Great

See ?hist For example hist(rnorm(100),plot=F,breaks=-3:3)$counts Regards Wayne -----Original Message----- From: Silvia Kirkman [mailto:silviakirkman@yahoo.com] Sent: 21 June 2004 14:01 To: r-help@stat.math.ethz.ch Subject: [R] frequencies Hi I have a set of fish lengths (cm) which I'd like to have divided into bins as specified by myself. I want to classify my bins as: 0<=x<0.5

Dear All, I would like to be able to estimate confidence intervals for a linear combination of coefficients for a GLS model. I am familiar with John Foxton's helpful paper on Time Series Regression and Generalised Least Squares (GLS) and have learnt a bit about the gls function. I have downloaded the gmodels package so I can use the estimable function. The estimable function is very

Dear all, I was trying to see how the function 'confint' is defined. Doing > confint function (object, parm, level = 0.95, ...) UseMethod("confint") <environment: namespace:stats> does not really enlighten me. How can I get to see the implementation (I guess it should be possible according to the general philosophy of the R project)? Thanks in advance S??ren

I am wondering how to obtain SE estimates for fixed effects from a nonlinear mixed effects model? I have fixed effects corresponding to three factors A, B and C with 2, 3 and 3 levels respectively. I have fit a model of the following general form: nlme1<-nlme(y~ SasympOrig(x, Asym, lrc), data=df, fixed=list(Asym~A*B*C, lrc~A*B*C), start=c(fixef(ETR.nlme)[1], rep(0,17), fixef(ETR.nlme)[2],

Thanks. I wonder if there is a general way of extracting var(u) and var(e), which would be needed to simulate u and e. Clearly, one can get the estimated parameters, but is there a clever way of 'setting up' the matrices?? Best S??ren On 6/19/05, S??ren H??jsgaard <Soren.Hojsgaard at agrsci.dk> wrote: > I would like to draw a sample from a linear mixed model y=Xb+Zu+e which has