similar to: Remove quotes from a string to use in a variable call

Displaying 20 results from an estimated 3000 matches similar to: "Remove quotes from a string to use in a variable call"

2003 Jan 30
1
as.formula(string) and augPred in lme
Using formulas constructed from strings only partially works for me in lme: library(nlme) data(Orthodont) fm2<-lme(as.formula("distance~age"),data=Orthodont,random=~1|Subject) summary(fm2) # works augPred(fm2) # fails #Error in inherits(object, "formula") : #Argument "object" is missing, with no default I assume that my use of as.formula is wrong, but
2009 Jun 25
2
Problems with subsets in NLME
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,
2004 Aug 27
2
degrees of freedom (lme4 and nlme)
Hi, I'm having some problems regarding the packages lme4 and nlme, more specifically in the denominator degrees of freedom. I used data Orthodont for the two packages. The commands used are below. require(nlme) data(Orthodont) fm1<-lme(distance~age+ Sex, data=Orthodont,random=~1|Subject, method="REML") anova(fm1) numDF DenDF F-value p-value (Intercept) 1
1999 Jun 02
1
lme problem ?
Dear friends. I tried the session below with 10 MB in both vsize and nsize but didn't get the example work. Is this a problem in LME or in me or both or somewhere else or undefined ? R : Copyright 1999, The R Development Core Team Version 0.64.0 Patched (May 3, 1999) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type
2005 Jun 08
0
bug in predict.lme?
Dear All, I've come across a problem in predict.lme. Assigning a model formula to a variable and then using this variable in lme (instead of typing the formula into the formula part of lme) works as expect. However, when performing a predict on the fitted model I gan an error messag - predict.lme (but not predictlm) seems to expect a 'properly' typed in formula and a cannot extract
2000 Jun 04
2
mle (PR#560)
Full_Name: Per Broberg Version: 1.00 OS: Windows 98 Submission from: (NULL) (62.20.231.229) I tested my installation with the following: > library(lme) Loading required package: nls Error in dyn.load(x, as.logical(local), as.logical(now)) : unable to load shared library "C:\PROGRAM\R\RW1000/library/nls/libs/nls.dll": LoadLibrary failure > data(Orthodont) > fm1
1999 Jun 02
0
Sv: lme problem ?
Dear Douglas Bates. I just downloaded the compiled version (I'm a poor Windows devil, not yet having found the time to move to a more advanced platform...) from NT- the files are dated 30.5-1999 so they are not old - and the problem persisted....wonder what I did wrong ? R : Copyright 1999, The R Development Core Team Version 0.64.0 Patched (May 3, 1999) R is free software and comes with
2017 May 10
2
bug report: nlme model-fitting crashes with R 3.4.0
lme() and gls() models from the nlme package are all crashing with R.3.4.0. Identical code ran correctly, without error in R 3.3.3 and earlier versions. The behavior is easily demonstrated using one of the examples form the lme() help file, along with two simple variants. I have commented the errors generated by these calls, as well as the lines of code generating them, in the code example below.
2009 Apr 07
3
write text file as output without quotes
Hi R, When I use the below to write the text file try=data.frame(rep("a",5), rep("b",5)) write.table(try,"z:\\try.txt",row.names=F,col.names=F,sep="\t") the output contains two columns with quotes! Is there a way to write without quotes? I tried try[,1]=noquote(try[,1]) try[,2]=noquote(try[,2]) Thank you, Regards, Ravi Shankar
1999 Nov 27
0
lme
Doug, I thought perhaps that you might be interested in the comparison of lme to the results for the same models fitted by Richard Jones' carma (I just wrote the R interface to his Fortran code). The code to run the example from the lme help and for the equivalent with carma is in the file below. The two main differences in results are 1. the random coefficients covariance matrix is quite
2000 Mar 07
1
Problems with nlme (PR#471)
Dear R developers, first of all let me join the chorus of congratulations for the release of R 1.0.0. Well, done! Unfortunately, I find it necessary to e-mail in a bug report regarding the `nlme' package. On my office machine I experience the following trouble: bossiaea:/opt/R$ R CMD check -c nlme Checking package `nlme' ... Massaging examples into `nlme-Ex.R' ... Running
2007 Dec 05
0
lme output
Dear all, I noticed the following in the call of lme using msVerbose. fm1 <- lme(distance ~ age, data = Orthodont, control = lmeControl(msVerbose=T)) 9 318.073: -0.567886 0.152479 1.98021 10 318.073: -0.567191 0.152472 1.98009 11 318.073: -0.567208 0.152473 1.98010 fm2 <- lme(distance ~ age, random =~age, data = Orthodont,
2008 Aug 28
1
Adjusting for initial status (intercept) in lme growth models
Hi everyone, I have a quick and probably easy question about lme for this list. Say, for instance you want to model growth in pituitary distance as a function of age in the Orthodont dataset. fm1 = lme(distance ~ I(age-8), random = ~ 1 + I(age-8) | Subject, data = Orthodont) You notice that there is substantial variability in the intercepts (initial distance) for people at 8 years, and that
2017 May 11
2
bug report: nlme model-fitting crashes with R 3.4.0
On 11 May 2017 at 10:17, Erwan Le Pennec wrote: | Dear all, | | I've stumbled a similar issue with the package cluster when | compiling the 3.4.0 version with the settings of Fedora RPM specs. | Compiling R with the default setting of configure yields a version that | works for cluster... and nlme. | | I did not find the exact option that was the cause of this issue | but
2020 Nov 05
1
Named class vector
The source to the noquote() function looks like this: noquote <- function(obj, right = FALSE) { ## constructor for a useful "minor" class if(!inherits(obj,"noquote")) class(obj) <- c(attr(obj, "class"), if(right) c(right = "noquote") else "noquote") obj } Notice what happens with right =
1997 Aug 20
1
R-alpha: R-0.50-a3(+) Method despatching bug ?
It is very wierd... Can some of you confirm the following behavior ? It is a new bug (feature ?) which was not yet in 0.49 ... noquote <- function(obj) { ## constructor for a useful "minor" class if(!inherits(obj,"noquote")) class(obj) <- c(class(obj),"noquote") obj } "[.noquote" <- function (x, subs) structure(unclass(x)[subs], class =
2017 Sep 19
0
remove quotes from matrix
Works fine for me. What do you object to in the following? Calling the above df "d", > dm <- as.matrix(d) > dm Sub_Pathways BMI_beta SAT_beta VAT_beta 1 "Alanine_and_Aspartate" " 0.23820" "-0.02409" " 0.94180" 2 "Alanine_and_Aspartate" "-0.31300" "-1.97510" "-2.22040" 3
2004 Apr 17
0
nlme - sum of squares - permutation test
Hi, 1/ I wonder why a anova.lme on a single lme object does not print the sum of squares (as expected from the help: "a data frame with the sums of squares, numerator degrees of freedom, denominator degrees of freedom, F-values, and P-values"). Example: > fm2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1) > anova(fm2) numDF denDF F-value p-value
2006 Oct 18
1
lmer- why do AIC, BIC, loglik change?
Hi all, I am having issues comparing models with lmer. As an example, when I run the code below the model summaries (AIC, BIC, loglik) differ between the summary() and anova() commands. Can anyone clear up what's wrong? Thank you! Darren Ward library(lme4) data(sleepstudy) fm1<-lmer(Reaction ~ Days + (1|Subject), sleepstudy) summary(fm1) fm2<-lmer(Reaction ~ Days +
2002 Dec 15
2
Interpretation of hypothesis tests for mixed models
My question concerns the logic behind hypothesis tests for fixed-effect terms in models fitted with lme. Suppose the levels of Subj indicate a grouping structure (k subjects) and Trt is a two-level factor (two treatments) for which there are several (n) responses y from each treatment and subject combination. If one suspects a subject by treatment interaction, either of the following models seem