similar to: package nlme

Hi R Users, When I use package lme4 for mixed model analysis, I can't distinguish the significant and insignificant variables from all random independent variables. Here is my data and result: Data: Rice<-data.frame(Yield=c(8,7,4,9,7,6,9,8,8,8,7,5,9,9,5,7,7,8,8,8,4,8,6,4,8,8,9), Variety=rep(rep(c("A1","A2","A3"),each=3),3),

Dear all, I am puzzled that how can i uninstall a R package that have been installed earlier (especially in MacOS). Any suggestion will be appreciated. -- Wenjun [[alternative HTML version deleted]]

Hi, R Users I find a problem in extracting the R-squared and P-value from the lm results described below (in Italic), *Residual standard error: 2.25 on 17 degrees of freedom* *Multiple R-squared: 0.001069, Adjusted R-squared: -0.05769 * *F-statistic: 0.01819 on 1 and 17 DF, p-value: 0.8943 * * * Any suggestions will be appreciated. Thanks. Wenjun [[alternative HTML version deleted]]

Just as an exercise I am tying to add colours to a geom_segment command. I can get one colour but not a sequence of colours. Can anyone suggest how I can get the green lines in the plot below to be different colours? I thought I could use a palatte of colours but that did not seem to work. Thanks ========================================================================= library(ggplot2) xx

Hello, I want to perform an lme on a database with this structure: ID Sequence Temperature Tumour Error 1 5 0 1 8.721872e-08 1 5 0 2 8.695348e-08 1 5 0 3 2.019604e-13 1 5 37 1

Hola! I am encountering the following problem, in a multilevel analysis, using glmmPQL from MASS. This occurs with bothj rw1062 and r-devel, respectively with nlme versions 3.1-38 and 3.1-39 (windows XP). > S817.mod1 <- glmmPQL( S817 ~ MIEMBROScat+S901+S902A+S923+URBRUR+REGION+ + S102+S103+S106A+S108+S110A+S109A+S202+S401+S557A+S557B+ + YHOGFcat,

Hi there, I have been trying to fit an NLME to my data. My dataset has two category levels - one is a fixed effect (level1) and one is a random effect (level2), though so far I have only experimented with the highest level grouping (fixed, level1), with the following code: mod1 <- nlme(H ~ a*(1-exp(-b*D^c)), data=sizes, fixed=a+b+c~factor(Loc), start=c(a=75,b=0.05,c=0.7)) This returns the

Hi, R Users, Can maintainer rename the package on F-Forge? Any suggestions will be appreciated. Wenjun -- Wenjun [[alternative HTML version deleted]]

Hi R Users, I want to distinguish different condition by different symbols by pch in function grid.points, but the symbols needed should be with solid or hollow, in this way only 21 to 25 in pch worked, is there any other symbols could be used like this? or does it exist any other way to draw symbols? Any suggestions will be appreciated. Best regards. -- Wenjun [[alternative HTML

Everyone - What do the NaN's mean here? Is this analysis a problem? Linear mixed-effects model fit by maximum likelihood Data: tmp.dat AIC BIC logLik 1611.251 1638.363 -797.6253 Random effects: Formula: ~1 | group_id (Intercept) Residual StdDev: 0.0003077668 9.236715 Fixed effects: AvgTrials ~ time + factor(group_id) + time * factor(group_id)

Dear R-community, I'm analysing some noise using the nlme-package. I'm writing in order to get my usage of lme verified. In practise, a number of samples have been processed by a machine measuring the same signal at four different channels. I want to model the noise. I have taken the noise (the signal is from position 1 to 3500, and after that there is only noise). My data looks like

Hi, the following R lines work fine in R 2.4.0, but not in R 2.4.1 or any devel versions of R 2.5.0 (see below for details). library(drc) # to load the dataset 'PestSci' library(nlme) ## Setting starting values sv <- c(0.43355869, 2.49963220, 0.05861799, 1.73290589, 0.38153146, 0.24316978) ## No error m1 <- nlme(SLOPE ~ c + (d-c)/(1+exp(b*(log(DOSE)-log(e)))), fixed =

Hello all, In lme4 if you want to model two non-nested random effects you code it like this: mod1 <- lmer(y~x + (1|randomvar1) + (1|randomvar2)) How would you go about to model something similar in nlme? In my database I have two variables for which I have repeated measures, lets call them "individual" and "year". But none of the "individuals" were measured in

Dear R users, Does anyone knows how to run a glmm with one fixed factor and 2 random numeric variables (indices)? Is there any way to force in the model a separate interaction of those random variables with the fixed one? I hope you can help me. #eg. Reserve <- rep(c("In","Out"), 100) fReserve <- factor(Reserve) DivBoulders <- rep

Hi, Please consider the following : x = c(1,3,NA,5) y = c(2,NA,4,1) min(x,y,na.rm=TRUE) # ok [1] 1 max(x,y,na.rm=TRUE) # ok [1] 5 sum(x,y,na.rm=TRUE) # ok [1] 16 pmin(x,y,na.rm=TRUE) # ok [1] 1 3 4 1 pmax(x,y,na.rm=TRUE) # ok [1] 2 3 4 5 psum(x,y,na.rm=TRUE) [1] 3 3 4 6 # expected result Error: could not find function "psum" # actual result

Dear all, predict.lme() throws an error when the fixed part consists of only an intercept and using newdata. See the reproducible example below. I've tracked the error down to asOneFormula() which returns in this case NULL instead of a formula. Changing NULL instead of ~1 in that function (see below) solves the problem in the case of an intercept only model (m1). It does not solve the problem

Hi all I'm trying to complete a textbook example originally designed for SPSS in R, and I therefore need to find out how to compute an unbalanced ANOVA in R. I did a search on the mailinglist archives an found a post by Prof. Ripley saying one should use the lme function for (among other things) unbalanced ANOVAs, but I have not been able to use this object. My code gives me an error.. Why

Dear all, I'm not getting what I'm doing wrong. The line below from my read.fsa.bin function throws an error when just loading my AFLP package and disappears when I load the zoo package as well. #the line that throws the error Index <- which(Peak == rollmax(Peak, k = 1 + 2 * floor((min(diff(SizeStandard)) * Fs - 1) / 2), fill = -Inf)) #the error Error in UseMethod("rollmax")

Hello, I have an unbalanced mixed model design with two fixed effects "site" (2 levels) and "timeOfDay" (4 levels) and two random effects "day" (3 consecutive days) and "trap" (6 unique traps, 3 per site). The dependent variable is the body length ("BL") of insect larvae from 7 to 29 individuals per trap (104 individuals in total). To account

Hi All, I am running an Rscript with a bunch of algorithms that are UNSTABLE under some parameter settings. At a certain point one of them sends error massage and my whole run STOPS! What I would like is to save the error massage in some file or variable and carry on to the next command line without stopping this run... Any help or ideas would be welcome, please, with a concrete example (not