similar to: str() to extract components

Can you provide the summary(m2) results? > -----Original Message----- > From: Simon Pickett [mailto:S.Pickett at exeter.ac.uk] > Sent: Wednesday, August 16, 2006 7:14 AM > To: Doran, Harold > Cc: r-help at stat.math.ethz.ch > Subject: [SPAM] - RE: [R] REML with random slopes and random > intercepts giving strange results - Bayesian Filter detected spam > > Hi again,

Hi everyone, I have been using REML to derive intercepts and coeficients for each individual in a growth study. So the code is m2 <- lmer(change.wt ~ newwt+(newwt|id), data = grow) Calling coef(model.lmer) gives a matrix with this information which is what I want. However, as a test I looked at each individual on its own and used a simple linear regression to obtain the same information, then

Hi all, I have been bumbling around with r for years now and still havent come up with a solution for plotting reliable graphs of relationships from a linear regression. Here is an example illustrating my problem 1.I do a linear regression as follows summary(lm(n.day13~n.day1+ffemale.yell+fmale.yell+fmale.chroma,data=surv)) which gives some nice sig. results Coefficients:

Hi, I would like to (if possible) set the default width and height for graphs at the start of each session and have each new graphic device overwrite the previous one. I only know how to do this using windows(width=,height=...) which opens up a new plotting device every time, so I end up with lots of graphs all over the place until I get the one I want! Thanks in advance, Simon Simon Pickett

Hi, I am an R beginner and having problems structuring my REML models. I have a model with y=weight x1=time x2=timesquared id=individual identity I need to structure the model such that in the random effects there is a constant intercept for all individuals but a separate individual slope for both x1 and x2 (a coefficient score for every individual).

Hi R experts, I have been using ReML as follows... model<-lmer(late.growth~mtf+year+treat+hatch.day+hatch.day:year+hatch.day:treat+ mtf:treat+ treat:year+ year:treat:mtf+(1|fybrood), data = A) then I wanted to plot the results of the three way interaction using lines() as follows... tmp<-as.vector(fixef(model)) graph1<-plot(mtf,fitted(f2), xlab=list("Brood Size"),

Hi all, I have been using princomp() recently, its very useful indeed, but I have a question about how to specify the rows of data you want it to choose. I have a set of variables relating to bird characteristics and I have been using princomp to produce PC scores from these. However since I have multiple duplicate entries per individual (each bird had a varying number of chicks), I only want

Hi R experts, I am interested on the effects of two dietry compunds on the growth of chicks. Rather than extracting linear growth functions for each chick and using these in an analysis I thought using ReML might provide a neater and better way of doing this. (I have read the pdf vignette("MlmSoftRev") and "Fitting linear mixed models in R" by Douglas Bates but I am not

Hello, I have a data frame that has three fields. Resp# ActCode ProdUsed 100 3 2 100 3 2 100 4 3 100 4 3 101 3 6 102 2 1 102 3 1 103 5 1 103 5 1 103

Hi! I fairly new to R, have only done pretty basic things so far, so this may be a very basic question..... But I did search the forums and didn't see a solution.... I'm trying to get going with kripp.alpha(). I'm loading data from a file, like this: > library(irr) Loading required package: lpSolve > x <- read.table("foo", comment.char="#", header=TRUE,

Dear All, I wonder if someone can point me in the right direction here. I'm working with the rms library, R 2.9.2 under Windows XP. I'm trying to arrange two plots side by side for a colleague. mfrow or mfcol do not seem to work, however, so I am obviously missing something important. I know that there have been changes in the graphics from Design to rms, but am just not sure where to

Hello everyone, I have successfully made an error bar graph using the points() command with the arrows() command to maually add on the standard errors. However, one slightly annoying feature of using this method is that the points dont line up exactly with the arrows (if you look carefully the points are never perfectly in the centre of the arrow), even when you move the arrows around in an

Hi, Thanks for your response, it nearly worked! But it only wrote one coloumn of data and not the three columns I need. Using fixef(m1) doesnt give the same results as coef(m1) when you are using more than one random effect. I need the coefficients for each individual so I use coef(m1) to get this which results in an object of class lmer.coef, 3 columns by 700 rows. as.data.frame() wont work on

Hi, I am an R newbie and one thing I am having trouble with binding variables that I have created within one data frame into a new data frame when using na.omit(). To illustrate this problem I will give the example I am working on and the approah I have been using:- data.frame1<-filepath.... attach(data.frame1) #create a new variable using a function new.variable<-rep(1,length(weight3))

Hi, I am trying to do fragment caching using :mem_cache_store. However, when I compare it to fragment caching using :file_store, it seems to be a lot slower. Here are the results: uncache Completed in 2.20246 (0 reqs/sec) | Rendering: 2.19891 (99%) | DB: 0.00017(0%) | 200 OK [ http://127.0.0.1/] using file_store Completed in 0.00952 (105 reqs/sec) | Rendering: 0.00702 (73%) | DB: 0.00000(0%)

Hi, Can anyone explain how the standard error in arima() is calculated? Also, how can I extract it from the Arima object? I don't see it in there. > x <- rnorm(1000) > a <- arima(x, order = c(4, 0, 0)) > a Call: arima(x = x, order = c(4, 0, 0)) Coefficients: ar1 ar2 ar3 ar4 intercept -0.0451 0.0448 0.0139 -0.0688 0.0010 s.e.

Building the current release 2.7 branch on x86_64-apple-darwin10 with r81455 reverted, I get the following Polyhedron 2005 benchmark results (with no test failures)... ================================================================================ Date & Time : 7 Apr 2010 22:24:16 Test Name : llvm_gfortran_lin_p4 Compile Command : llvm-gfortran -ffast-math -funroll-loops -msse3

Dear MCMCglmm users, I am currently struggling with the specification of a proper prior and model formula for a multi-response MCMCglmm with two of the three response variables being Gaussian and the third being za-poisson. The model includes several fixed effects and three nested random effects. In general, I would prefer to fit a model with a fixed effect of trait and suppressed intercept for

On Apr 7, 2010, at 8:41 PM, Jack Howarth wrote: > Building the current release 2.7 branch on x86_64-apple-darwin10 > with r81455 reverted, I get the following Polyhedron 2005 benchmark > results (with no test failures)... Very nice! A 14% speedup on a benchmark we don't tune for isn't bad. I imagine that there are several easy wins you could get on it if you were interested

I have been using lmer in lme4() to analyse the effect of dropping a term from the model as below anova.name<-anova(m1,m2) Where m1 is an original model and m2 has one term removed. I can then create my own type III tables for each variable in the model. However with many variables this becomes exceedingly time consuming! anova.lme in nlme() and Anova() in car dont seem to work for lme