search for: fator

Hi, I make this model using lme m.lme <- lme(Glycogen~Treatment,random=~1|rTrt/Liver) How to make this using lmer? I try > m.lmer <- lmer(Glycogen~Treatment+(1|rTrt/Liver)) Erro em lmer(Glycogen ~ Treatment + (1 | rTrt/Liver)) : entry 0 in matrix[0,0] has row 2147483647 and column 2147483647 Al??m disso: Mensagem de aviso: / not meaningful for factors in: Ops.factor(rTrt, Liver)

Hello, I have a small test case : a = b * c + b * d and clang is fatorizing b to get only one multiplication (-O3) which is normally good for most architectures. But in my case, that pattern takes just one instruction and I would like to recover it as is. Where can I find this particular optimization in clang ? Is there a way of setting multiplications as being chea...

...(a has 2 levels, b has 3 levels). I have an object kidney.aov which is an aov(y ~ a*b), and when I ask for model.tables(kidney.avo, se=T) I get the following message along with the table of effects: Design is unbalanced - use se.contrast() for se's but the design is NOT unbalanced... each fator level combination has the same n I' d appreciate any help. Thanks.

Le 5 janv. 2012 à 15:59, Ivan Llopard a écrit : > Hello, > > I have a small test case : > > a = b * c + b * d > > and clang is fatorizing b to get only one multiplication (-O3) which is > normally good for most architectures. But in my case, that pattern takes > just one instruction and I would like to recover it as is. > Where can I find this particular optimization in clang ? > Is there a way of setting multiplic...

...n package) object graph. I was able to move the labels with the coding below, but it moves the entire vector... CAPobj<-CAPpotiFT for(i in c(2:8))CAPobj$CCA[[i]][,1]<-CAPpotiFTI$CCA[[i]][,1] CAPpotiFTI$CCA[[i]][,1][2]<-0.85 And here the graphic script ScoresCAPFT<-scores(CAPpotiFTI) FatoresRep<-read.xls('Fatores.xls',sheet=1,rowNames=T) plot.cca(CAPpotiFTI,type='none',display=c('bp','sites'),main='Total Fauna - Sites vs. Environment') points(ScoresCAPFT$sites[FatoresRep$BiofaciesBC=='1',],pch=21) points(ScoresCAPFT$sites[FatoresRep$...

...a to solve it? Thank you for your attention and patience Sorry if the English is not that good, I'm Brazilian. Here is the script I'm using! # The analysis library(vegan) library(xlsReadWrite) PotiAbio<-read.xls('PotiAbioCanoco.xls',sheet=1,rowNames=T) PotiBio<-read.xls('FatorialReplica.xls',sheet=8,rowNames=T) attach(PotiAbio) LogPotiBio<-log(PotiBio+1) dbRDA<-capscale(t(LogPotiBio)~"Environmental Variables",dist="bray",add=T) dbRDA #Preparing to generate and save the graphic SymbolsRep<-read.xls('Fatores.xls',sheet=2) tiff('...

...a to solve it? Thank you for your attention and patience Sorry if the English is not that good, I'm Brazilian. Here is the script I'm using! # The analysis library(vegan) library(xlsReadWrite) PotiAbio<-read.xls('PotiAbioCanoco.xls',sheet=1,rowNames=T) PotiBio<-read.xls('FatorialReplica.xls',sheet=8,rowNames=T) attach(PotiAbio) LogPotiBio<-log(PotiBio+1) dbRDA<-capscale(t(LogPotiBio)~"Environmental Variables",dist="bray",add=T) dbRDA #Preparing to generate and save the graphic SymbolsRep<-read.xls('Fatores.xls',sheet=2) tiff('...

...---------------------------------- > n2 <- nls(y~model(x, A[tr], B[tr]), data=da, + start=list(A=c(10,10), B=c(3,3)), trace=TRUE) 0.2446993 : 10 10 3 3 0.2366604 : 9.887467 9.916289 3.000000 3.000000 Erro em nls(y ~ model(x, A[tr], B[tr]), data = da, start = list(A = c(10, : fator de passos 0.000488281 reduzido abaixo de 'minFactor' de 0.000976562 #------------------------------------------------------------ That indicates the categorical variable was accounted. But values of B didn't change during iteration. Why? Thanks, Walmes. ==============================...