similar to: Modifying Code in .rda based packages (e.g. lme4)

Displaying 20 results from an estimated 10000 matches similar to: "Modifying Code in .rda based packages (e.g. lme4)"

2010 Mar 20
5
Problem specifying Gamma distribution in lme4/glmer
Dear R and lme4 users- I am trying to fit a mixed-effects model, with the glmer function in lme4, to right-skewed, zero-inflated, non-normal data representing understory grass and forb biomass (continuous) as a function of tree density (indicated by leaf-area). Thus, I have tried to specify a Gamma distribution with a log-link function but consistently receive an error as follows: >
2004 May 28
1
Pr(>|z|) in lme4
Dear List, I am struggling understanding S4 classes. For example, when GLMM summary(glmmML( whatever)) outputs the following line: Estimate Std. Error DF z value Pr(>|z|) (Intercept) 0.856 0.319 45 2.68 0.0073 How do I access the Pr column? Dieter
2007 Oct 05
1
R 2.6.0 Windows/lme4 Rblas load problem
Dear Windows Maintainers, after installing R 2.6.0 on Windows 2000 and doing a complete update of the libraries as recommended by B.Ripley, it get the error message: The dynamic link library Rblas could not be found in the specified path.... Note that the message says "Rblas", not Rblas.dll as expected under Windows. The path is correct, and Rblas.dll is present I made a copy of
2006 Jan 12
1
"infinite recursion" in do.call when lme4 loaded only
A larg program which worked with lme4/R about a year ago failed when I re-run it today. I reproduced the problem with the program below. -- When lme4 is not loaded, the program runs ok and fast enough -- When lme4 is loaded (but never used), the do.call fails with infinite recursion after 60 seconds. Memory used increases beyond bonds in task manager. -- I tested a few S3 based packages
2006 Jan 12
1
"infinite recursion" in do.call when lme4 loaded only
A larg program which worked with lme4/R about a year ago failed when I re-run it today. I reproduced the problem with the program below. -- When lme4 is not loaded, the program runs ok and fast enough -- When lme4 is loaded (but never used), the do.call fails with infinite recursion after 60 seconds. Memory used increases beyond bonds in task manager. -- I tested a few S3 based packages
2006 Oct 09
1
Transcript of "Conservative ANOVA tables"
Dear friends of lmer, http://wiki.r-project.org/rwiki/doku.php?id=guides:lmer-tests I have put a transcript of the long thread on lmer/lme4 statistical test into the Wiki. For all those who missed it life, and for those like me, who don't like the special style of the R-list to keep full length quotes. Creating the text there was not much fun, waiting times are simply unacceptable and the
2002 Jul 16
2
r-square for non-linear regression
We have extracted parameters from physiological measurements by fitting SSlogis-like curves with nlsList and nlme. We presented residuals plot in a paper, but a referee argues that these cannot be included (too technical), and r-square values should be given instead to compare the goodness of fit with those of other authors. I remember that 30 years ago in my stat 101, I learned that r-square is
2001 Mar 01
2
Individual rename of list items
I am confused by the logic of renaming: # Rename individual list items? Empl<-list(employee="Anna",spouse="Fred") names(Empl)<-c("empl","spo") names(Empl) #[1] "empl" "spo" # worked like a charm... but names(Empl[1])<-"newempl" # no error message, yet .... names(Empl) #[1] "empl" "spo" #
2001 Feb 27
2
Remove columns by name data[-c("subj","drug")]
Is there an easy way to remove data frame columns by name instead of by index? The following gives the idea remove<-c("subj","drug") data[-remove] I found a solution with a few evals and substitutes, similar to that used in reshapeLong, but there must be an easier way out. Dieter --------------------------------------- Dr. Dieter Menne Biomed Software 72074 T?bingen Tel
2008 Dec 22
3
Convert ASCII string to Decimal in R (vice versa) was: Hex
Hi Dieter, Sorry my mistake. I wanted to convert them into Decimal (not Hexadecimal). Given this string, the desired answer follows: > ascii_str <- "ORQ>IK" 79 82 81 62 73 75 > ascii_str2 <- "FDC" 70 68 67 - Gundala Viswanath Jakarta - Indonesia On Mon, Dec 22, 2008 at 5:49 PM, Dieter Menne <dieter.menne at menne-biomed.de> wrote: > Gundala
2011 Jul 28
2
not working yet: Re: lattice overlay
Hi Dieter and R community: I tried both of these three versions with ylim as suggested, none work: I am getting only single (pch = 16) not overlayed (pch =3) everytime. *vs 1* require(lattice) xyplot(Sepal.Length ~ Sepal.Width | Species , data= iris, panel= function(x, y, subscripts) { panel.xyplot(x, y, pch=16, col = "green4", ylim = c(0, 10)) panel.lmline(x, y, lty=4, col =
2002 Jun 20
1
Psychometric curves, two altnerative force choice, glm, and budbworms
Dear R-Listers, to measure the psychometric curve of pitch discrimination, one sequentially presents two tones of slightly different pitch to an observer (animal will do), and asks "which is higher". The pschometric curve is the fraction of correct responses plotted against the pitch difference. It passes through 50% (pure guessing) at zero and normally approaches 100% at large
2001 Feb 23
1
as.formula and lme ( Fixed effects: Error in as.vector(x, "list") : cannot coerce to vector)
Using a formula converted with as.formula with lme leads to an error message. Same works ok with lm, and with lme and a fixed formula. # demonstrates problems with lme and as.formula demo<-data.frame(x=1:20,y=(1:20)+rnorm(20),subj=as.factor(rep(1:2,10))) demo.lm1<-lme(y~x,data=demo,random=~1|subj) print(summary(demo.lm1)) newframe<-data.frame(x=1:5,subj=rep(1,5))
2001 Feb 04
1
quinModel S != R
Dear friends of nlme, Running quinModel (Pinheiro/Bates page 380) on R (current release, windows) gives: Nonlinear mixed-effects model fit by maximum likelihood Model: conc ~ quinModel(Subject, time, conc, dose, interval, lV, lKa, lCl) Data: Quinidine Log-likelihood: -497 Fixed: lV + lKa + lCl ~ 1 lV lKa lCl 5.382 -0.273 2.470 Random effects: Formula: list(lV ~ 1, lCl ~ 1)
2005 Apr 06
2
par(mfcol=2, mfrow=3) equivalent for trellis
Dear friends of lattice, I know how to position trellis plots with print(...,split,more=T) or (...position). Sometimes I wish I had something like the old "par(mfcol=2, mfrow=3)" mechanism, where the next free viewport is automatically chosen. I tried fiddling with grid-viewports, but could not find an easy solution. Did I miss something? Dieter Menne
2002 May 27
1
nlme cross-over and fixed nested
I have problem getting the concept of a nested fixed variable into the nlme scheme. I fear the question is very stupid. In the past I had asked this before, and never got a reply (in other cases, the response was within hours). I also checked the S-list, where several similar enquiries of other people are orphaned. We have a cross-over design, where patient are treated two weeks with placebo,
2009 Apr 20
1
Buglet in plotCI
Dieter Menne wrote: > Hi, Jim, > > there is a typo at the bottom of plotCI: there is an y.to.in which should be > x.to.in. > > See list for an example. > > http://article.gmane.org/gmane.comp.lang.r.general/147103 > > Should be: > nz <- (abs(ui - pmin(x + gap, ui)) * x.to.in) > 0.001 > > Dieter > > Hi Dieter, Thanks for the fix. I have
2005 Feb 08
2
lme4 --> GLMM
hello! this is a question, how can i specify the random part in the GLMM-call (of the lme4 library) for compound matrices just in the the same way as they defined in the lme-Call (of the nlme library). For example i would just need random=list(my.Subject=pdBlocked(list(pdIdent(~... , ...),pdIdent(~... , ...)))) this specification , if i also attach library(nlme) , is not
2005 Feb 08
2
lme4 --> GLMM
hello! this is a question, how can i specify the random part in the GLMM-call (of the lme4 library) for compound matrices just in the the same way as they defined in the lme-Call (of the nlme library). For example i would just need random=list(my.Subject=pdBlocked(list(pdIdent(~... , ...),pdIdent(~... , ...)))) this specification , if i also attach library(nlme) , is not
2005 Jul 04
1
A faster way to aggregate?
Dear List, I have a logical data frame with NA's and a grouping factor, and I want to calculate the % TRUE per column and group. With an indexed database, result are mainly limited by printout time, but my R-solution below let's me wait (there are about 10* cases in the real data set). Any suggestions to speed this up? Yes, I could wait for the result in real life, but just curious if I