search for: hist1

anyone know how to add text in the Trellis plot panel ?? i want to add things eg: dot dot dot. in the headrer of the panel. eg: http://old.nabble.com/file/p26486579/hist1.png hist1.png -- View this message in context: http://old.nabble.com/Trellis-Plot-tp26486579p26486579.html Sent from the R help mailing list archive at Nabble.com.

Dear All, I have a massive dataset from which I would like to draw a histogram. Any ideas on how to accomplish this? Thanks in advance, Paul

Appologies if this has been addressed before, but I can't seem to find it in the help archives. I'm looking to do something like the following but it looks like save.plot is deprecated. save.plot(plot(glm1$residuals,gain,main = "Hist of residuals and gain"),file="Desktop/hist1.png") Thanks in advance, Sean Session Info: R version 2.9.1 (2009-06-26) i386-apple-darwin8.11.1 locale: en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] stats graphics grDevices utils datasets methods base loaded via a namespace (and not atta...

...l cross breakdown. Other suggestions welcome. Note that in the output there should be empty fields on repeated column values like ftable produces. Dieter #--------------------------------------- library(Hmisc) df = data.frame(drug=sample(c("P","V"),100,TRUE), Hist1=sample(c("Pos","Neg"),100,TRUE), Hist2=sample(c("Pos","Neg"),100,TRUE)) ftable(drug~Hist1+Hist2,data=df)

Rhelpers: I'm curious what the appropriate analysis to use for testing the hypothesis that two histograms are statistically different from one another? Thanks! --j

...not equal, and therefore I have tried to apply the classical transformations to have homocedasticity in order to be able to use ANOVA. Unfortunately, no transformation that I have used transforms my data into data with homocedasticity. The histogram of variances is at http://phhs80.googlepages.com/hist1.png Is someone able to suggest to me a transformation to overcome the problem of heterocedasticity? Thanks in advance, Paul

Hi, Using S=1000 and simdata <- replicate(S, generate(3000)) #If you want both "m1" and "m0" #here the missing values are 0 res1<-sapply(seq_len(ncol(simdata.psm1)),function(i) {x1<-merge(simdata.psm0[,i],simdata.psm1[,i],all=TRUE); x1[is.na(x1)]<-0; x1}) res1[,997:1000] #????? [,1]???????? [,2]???????? [,3]???????? [,4]??????? #x1??? Numeric,3000 Numeric,3000