similar to: ppr, number of terms, and data ordering

Dear R listers -- The program below does the following tasks: 1. It creates a file (wintemp4) that is a subset of alldata4 consisting of "winner" records in 50 industry groups (about 5400 obs); 2. It defines a function (myppr1) that runs the ppr function in modreg once to generate goodness of fit (sum of squared errors) measures by number of terms included in model and then reruns

Sorry about the lack of detail. I am running R v.1.2.2. I can recast my question (which I think I have partially answered) more succinctly as follows: 1. This seems to work (note that group takes values 1,2,3,4, or 5): my.newfun <- function(x) myfile <- lm(award ~ ilogemp + ilogage, x) test.by <- by(wintemp, as.factor(wintemp$group), my.newfun) 2. This does not work (leaving aside

Dear R list: I want to make separate estimates for each level of the variable "group." After consulting many sources I am stumped as to why the following does not work: > wintemp <- subset(alltemp, winner==1) > my.ppr <- function(x) + { + if(nrow(x) >= 50) { + pprfile <- ppr(award~ilogemp, data=x,nterms=5,max.terms=10,optlevel=3) + summary(pprfile) +

I used the supersmoother function in the modreg package as follows: super <- supsmu(ilogemp,award) Then I decided that I might want additional explanatory variables (other than ilogemp) in my model. The ppr function in modreg seemed a logical extension of supsmu from univariate to multidimensional explanatory variables. As a "check" I ran the following: pprest <-

Dear all, I have been doing tests using SVM, random forests and PPR. The data is from a data stream (that is, the data for training and for test is always increasing / changing). With SVM and random forests everything is ok, but with ppr there are situations where it crashes. For the examples I have used I noticed that if one of the variables has just one value (it can happen), it crashes for

Dear R users, I am looking for the source code of the implementation of ppr (Projection Pursuit Regression) in R. It will be great if citations of the source papers on which the implementation is based, are also provided. Thank you, Arvind Iyer, Grad student, Deptt. of Biomedical Engineering Viterbi School of Engineering University of Southern California, Los Angeles [[alternative HTML

Folks, The projection pursuit regression function in the base R seems to crash when the optimization level is set to zero, i.e. the initial ridge terms are accepted without refitting. I encountered this problem in an out-of-sample prediction exercise using predict. But further investigation suggests the issue is with the ppr fit and predict just sppeds up the crash. The other optlevels seem to be

Hi, Recently, I installed the 1.1.0 version of R (for Windows), since it includes an implementation of Projection Pursuit (I failed to write my own version of PP as a standalone C++ program). As far as I know, R offers two interfaces/sintax for the ppr() function. The first one requieres a regression formula and a data frame. The other requieres X, a matrix with the explanatory variables, and Y,

Full_Name: Hugh Miller Version: 2.8.1 OS: XP Submission from: (NULL) (128.250.24.101) Hi there, I've been looking at approaches that use the projection pursuit regression function fairly (ppr) heavily, and have discovered that it crashes my R system on occasion. It only happens with the inputs are pathological in some way I don't understand. I have pasted such an example below. Any

predict.lm(..., type="terms") gives wrong standard errors. Below, I have provided what I believe are the necessary fixes. However, there are subtleties, and the code needs careful checking. Some of the looping is surely not necessary, but it is surely best to begin with the minimum necessary changes. My tests, including checks against S-PLUS, have extended to fitting spline curves. I

>From e980153 Tue Apr 25 14:42:27 2000 To: r-help@stat.math.ethz.ch Subject: Wrong SEs in predict.lm(..., type="terms") For what it is worth, I am using RW-1.0.0 under Windows 98. I submitted this earlier to r-help. There is one change below to my proposed corrected code: predict.lm(..., type="terms") gives wrong standard errors. Below, I have provided what I believe are

Full_Name: Yves Rosseel Version: 2.2.1 OS: i686-pc-linux-gnu Submission from: (NULL) (157.193.116.152) Dear developers, For the single-model case, the anova.mlm() function does not seem to handle multi-parameter predictors (eg factors) correctly. A toy example illustrates the problem: Y <- cbind(rnorm(100),rnorm(100),rnorm(100)) A <- factor(rep(c(1,2,3,4), each=25)) fit <- lm(Y ~ A)

I'm trying to cross-compile R on a Mac OS X box to target Win32. It works quite well, everything works, except for one fortran file ppr.f in the stats package: ---------- Making package stats ------------ adding build stamp to DESCRIPTION installing NAMESPACE file and metadata making DLL ... i386-mingw32-g77 -O2 -Wall -c ppr.f -o ppr.o ppr.f:803: sorry, unimplemented: data

I'm trying to cross-compile R on a Mac OS X box to target Win32. It works quite well, everything works, except for one fortran file ppr.f in the stats package: ---------- Making package stats ------------ adding build stamp to DESCRIPTION installing NAMESPACE file and metadata making DLL ... i386-mingw32-g77 -O2 -Wall -c ppr.f -o ppr.o ppr.f:803: sorry, unimplemented: data

Hi all, I am doing a projection pursuit regression using the ppr() function from modreg. I would also like to use predict.ppr(). However, I cannot find any information about it in the help files. There is a link to predict.ppr in the index for modreg, but that link is to the help for ppr(). Has predict.ppr() not been implemented? If not, does anyone have a suggestion as to how to implement

supsmu(periodic=TRUE) can crash R by reading before start of array. To reproduce: set.seed(1) xx <- runif(29000) yy <- rnorm(29000) span <- 0.49 i <- 1 while(i < 200){ cat(i,"\n") int <- supsmu(xx,yy,periodic=T,span=span) i <-i+1 } results in: 1 2 3 4 5 6 7 8 9 Program received signal SIGSEGV,

Hopefully the last patch from me to UTF-8 issues. Metaflac can now print all console supported characters from tags on the screen. It also fixes metaflac to be able to import its own exports back without non-ascii characters getting mutilated. And --no-utf8-convert now works properly with import and export commands. I updated my Windows binary archive with these changes for any interested

The pursuit projection packages ppr is an excellent contribution to R. It is great for one-to-three ridge fits, often somewhat intuitive, and for multi-ridge fits, where it at least describes a lot of variance. Like many folk, I need to report the fits obtained from ppr to the greater, outside, non-R world. It is fairly obvious how to use the terms alpha and beta to report on

Hello again! Thanks to Dr. Brian Ripley, the make problem I reported earlier has been solved, and R-0.64.1 is now successfully installed and tested. There were two essential problems with the stock configuration: (i) the Fortran option -fPIC was not being propagated to certain Makefiles further down the tree; (ii) gmake was not being recognized when the library files were being

I've rolled up R-1.1.0.tgz a moment ago. You can get it from ftp://cvs.r-project.org/pub/CRAN/src/base/R-1.1.0.tgz or http://cvs.r-project.org/pub/CRAN/src/base/R-1.1.0.tgz or wait for it to be mirrored at a CRAN site near you within a day or two. There's also a version split in three for floppies if you prefer that. For the R Core Team, Peter D. Here's the relevant bit