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Hello -- I posted this question yesterday and for some reason the post seems to be attached to the wrong thread. Also, I extended my test a little and it seems to indicate the problem is with spm. I would appreciate any help. Thanks. ========================================================== library(plyr) library(SemiPar) data <-

plyr is a set of tools that solves a common set of problems: you need to break a big problem down into manageable pieces, operate on each pieces and then put all the pieces back together. It's already possible to do this with split and the apply functions, but plyr just makes it all a bit easier with: * consistent names, arguments and outputs * input from and output to data.frames,

plyr is a set of tools that solves a common set of problems: you need to break a big problem down into manageable pieces, operate on each pieces and then put all the pieces back together. It's already possible to do this with split and the apply functions, but plyr just makes it all a bit easier with: * consistent names, arguments and outputs * input from and output to data.frames,

I aggregated my data: aggresults <-aggregate(results, by=list(results$a, results$b, results$c), FUN=mean, na.rm=TRUE) results has about 8000 lines of data, and aggresults has about 80 lines. I would like to create a separate variable for each of the 80 aggregates, each containing the 100 lines that were aggregated. I would also like to create plots for each of those 80 datasets. Is

Dear R users, I am trying to write myself a loop in order to produce a set of 20 length frequency plots each pertaining to a factor level. I would like each of these plots to be available on the same figure, so I have used par(mfrow = c(4, 5)). However, when I run my loop below, it produces 20 plots for each factor level and only displays the last factor levels LF plots. I'm fairly new to

Dear R helpers, Last week Mr. Ista Zahn has taken lots of efforts and helped me with the following code generating basel_asset_wise (e.g. bank, corporate, sovereign) graphs. The code works excellently and assetwise grahs are aslo genereated. I have tried to customize the code as per my need. However, there is only one small problem with the graphs. The graph doesn't give me the asset names.

Dear R helpers, I have following data.frame giving asset class (i.e. bank, corporate, sovereign etc. as there could be number of classes) and rating-wise default frequency. I need to plot graphs for each of these classes i.e. bank, corporate and sovereign where I will be plotting ratings (AAA, AA, etc) on the x-axis and their respective default probabilities on Y-axis. I have tried to write a

Hello, I have longitudinal data of the form below from N subjects; I am trying to create figure with N small subplots on a single page, in which each plot is from only one subject, and in each plot there is a separate curve for each value of param1. So in this case, there would be four plots on the page (one each for Bob, Steve, Kevin and Dave), and each plot would have two separate curves (one

Dear all, I have a question regarding the possibility of parallel computation in plyr version 1.7. The help files of the following functions mention the argument '.parallel': ddply, aaply, llply, daply, adply, dlply, alply, ldply, laply However, the help files of the following functions do not mention this argument: ?d_ply, ?aply, ?lply Is it because parallel computation is not

plyr is a set of tools for a common set of problems: you need to break down a big data structure into manageable pieces, operate on each piece and then put all the pieces back together. For example, you might want to: * fit the same model to subsets of a data frame * quickly calculate summary statistics for each group * perform group-wise transformations like scaling or standardising *

plyr is a set of tools for a common set of problems: you need to break down a big data structure into manageable pieces, operate on each piece and then put all the pieces back together. For example, you might want to: * fit the same model to subsets of a data frame * quickly calculate summary statistics for each group * perform group-wise transformations like scaling or standardising *

There are a few version of apply() (e.g., lapply(), sapply()). I'm wondering if there is one that does not return anything but just silently apply a function to the list argument. For example, the plot function is applied to each element in 'alist'. It is redundant to return anything from apply. apply(alist,function(x){ plot each element of alist})

So I have a text file that looks like this: "Label" "X" "Y" "Slice" 1 "Field_1_R3D_D3D_PRJ_w617.tif" 348 506 1 2 "Field_1_R3D_D3D_PRJ_w617.tif" 359 505 1 3 "Field_1_R3D_D3D_PRJ_w617.tif" 356 524 1 4 "Field_1_R3D_D3D_PRJ_w617.tif" 2 0 1 5 "Field_1_R3D_D3D_PRJ_w617.tif" 412 872 1 6

If I have data: dat<-data.frame(a=rnorm(20),b=rnorm(20),c=rnorm(20),d=rnorm(20),site=rep(letters[5:8],each=5)) And want to plot like this: ctr<-1 for(i in c('a','b','c','d')){ png(file=paste('/tmp/plot_number_',ctr,'.png',sep=''),height=8.5, width=11,units='in',pointsize=9,res=300) print(ggplot(dat[,names(dat) %in%