similar to: unorder an ordered factor

Hello; I am having a problems with the interpretation of models using ordered or unordered predictors. I am running models in lmer but I will try to give a simplified example data set using lm. Both in the example and in my real data set I use a predictor variable referring to 3 consecutive days of an experiment. It is a factor, and I thought it would be more correct to consider it ordered. Below

I'm trying to change an unordered factor into an ordered factor: data96$RV961327 <- data96$V961327 data96$RV961327[data96$V961327 %in% levels(data96$V961327)[4]] <- NA data96$RV961327[data96$V961327 %in% levels(data96$V961327)[5]] <- NA data96$RV961327 <- factor(data96$RV961327) attributes(data96$RV961327) levels(data96$RV961327) data96$RV961327 data96$RRV961327 <-

I don't understand under what situation ordered factor rather than unordered factor should be used. Could somebody give me some examples? What are the implications of order vs. unordered factors? Could somebody recommend a textbook to me?

Dear R helpers, I'm trying to recode an ordered factor to reverse its scale, but I can't figure out how to make it. I am using the Recode function provided by the Car package. I've created an ordered variable: data$o.var1 <- ordered(data$var1, levels=c(1,2,3,4), labels =c("very satisfied", "fairly satisfied", "not very satisfied", "not at all

I am doing cluster analysis [hclust(Dist, method="average")] on data that potentially contains redundant objects. As expected, the inclusion of redundant objects affects the clustering result, i.e., the data a1, = a2, = a3, b, c, d, e1, = e2 is likely to cluster differently from the same data without the redundancy, i.e., a1, b, c, d, e1. This is apparent when the outcome is visualized

Please excuse me for asking such basic questions: Here is my code > y=c(1.21,0.51,0.14,1.62,-0.8,0.72,-1.71,0.84,0.02,-0.12) > ybar=mean(y) > ll=length(y); > ybarv=rep(ybar,ll) > x=1:ll > plot(x,ybarv,pch=1) > segments(x[1],ybar,x[ll],ybar) What I get is a collection of small circles, with a segment "on top" of the circles, which is almost what I want. But I

Hi All, I noticed LLVM target independent side is converting an ordered less than "setolt" into unordered greater than "setuge" operation. There are no target hooks to control going from the ordered mode into unordered. I am trying to figure out the best way to support unordered operation on Hexagon. We don't have a single instruction to do unordered operation. So we

I am working with Sweave and would like to print out into my latex document the result of the R command version$platform So what I first tried in my .Rnw document was \Sexpr{print(version$platform)}. However, the output from this command is the string "x86_64-apple-darwin10.8.0" (without the quotes). This contains an underscore, which is a special character in tex and so I get an error

On Tue, Jul 9, 2013 at 3:00 PM, <sundeepk at codeaurora.org> wrote: > Hi All, > > I noticed LLVM target independent side is converting an ordered less than > "setolt" into unordered greater than "setuge" operation. There are no > target hooks to control going from the ordered mode into unordered. > > I am trying to figure out the best way to support

Dear all, ? I don't know if you consider this a bug or feature, but it breaks reasonable code: 'unlist' and 'sapply' convert 'ordered' to 'factor' even if all levels are equal. Here is a simple example: o <- ordered(letters) o[[1]] lapply(o, min)[[1]]??????????# ordered factor unlist(lapply(o, min))[[1]]? # no longer ordered sapply(o, min)[[1]]??????????# no

On 29 August 2013 10:12, Demikhovsky, Elena <elena.demikhovsky at intel.com> wrote: > But this is another case. LLVM IR distinguishes between ordered and unordered compare and X86 backend has appropriate instructions. I think LLVM uses ordered/unordered compare to mean something different to what the x86 instructions do. For example, "not equal": fcmp une == unordered not

But this is another case. LLVM IR distinguishes between ordered and unordered compare and X86 backend has appropriate instructions. But during DAG selection we just lose this information and always generate unordered fcmp. I.e. in case of ordered fcmp the vcomiss should be generated, and in case of unordered - vucomiss. - Elena -----Original Message----- From: Dr D. Chisnall [mailto:dc552 at

Dear all, I do not seem to grasp how contrasts are set for ordered factors. Perhaps someone can elighten me? When I work with ordered factors, I would often like to be able to reduce the used polynomial to a simpler one (where possible). Thus, I would like to explicetly code the polynomial but ideally, the intial model (thus, the full polynomial) would be identical to one with an ordered factor.

> The function ISD::getSetCCInverse() would probably be useful for you > here: you can use it to transform an unordered operation into an > ordered operation. Thanks for your reply Eli. I will check how to convert unordered operations back to ordered one. I have another related question - is it possible for frontend (clang) to generate unordered operation from the source code? -Sundeep

Dear all, I am still a R apprentice... Apologies for the basic question. I am trying to reshape a dataframe based on the order of two variables (a character variable and a numerical variable). To simplify it, consider the following dataframe > df<-data.frame(id=c("b","b","a","a","a"),ord=c(2,1,1,3,2)) id ord 1 b 2 2 b 1 3 a 1 4

Suppose x and y are numeric vectors of the same length. plot(x,y) #scatterplot lmObj1 <- lm(y~x) # best fit line abline(lmObj1) # good lmObj2 <- lm(x~y) #get best fit but with axes interchanged abline(lmObj2) # not what I want. I want the correct line, drawn on the same graph, but with # response and predictor variables interchanged One way to proceed would be to

Should I open a ticket for this? - Elena From: Eli Friedman [mailto:eli.friedman at gmail.com] Sent: Wednesday, August 28, 2013 19:51 To: Demikhovsky, Elena Cc: llvmdev at cs.uiuc.edu Subject: Re: [LLVMdev] Ordered / Unordered FP compare are not handled properly on X86 On Wed, Aug 28, 2013 at 2:16 AM, Demikhovsky, Elena <elena.demikhovsky at intel.com<mailto:elena.demikhovsky at

[I hope all of you had some good holidays/vacation!] My current flabbergaster: ## a dummy factor > size<- rep( c('short', 'long'), 10 ) ## take a subset: > subset( size, size!='short') [1] "long" "long" "long" "long" "long" "long" "long" "long" "long" "long" ##

Dear All, Assume I have a data.frame that contains also factors and I would like to get another data.frame containing the factors as numeric vectors, to apply functions like sapply(..., median) on them. I read the warning concerning as.numeric or unclass, but in my case this makes sense, because the factor levels are properly ordered. I can do it, if I write for each single column

I found that there is no diff in code generator for Ordered / Unordered FP compare instructions. FUCOMISS, FUCOMISD are generated in the both cases. - Elena --------------------------------------------------------------------- Intel Israel (74) Limited This e-mail and any attachments may contain confidential material for the sole use of the intended recipient(s). Any review or