similar to: Re: help with R/S functions on nonpar. regression

I now have versions of code that is destined (I believe) for 0.63 which is in a suitable state for comment. The files are at ftp://ftp.stats.ox.ac.uk/pub/R (Our www server is being moved, so may be intermittently down, but this ftp server should be stable.) All are R packages, for the moment for personal use only (no re-distribution). Use with 0.62.3 or 0.63 (although I am aware of some

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 <-

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

Hi has anyone succeeded in installing R on DEC alpha OSF 4.0 with gcc/g77 ? The PLATFORMS file mentions successful installtion on OSF 3.2 using cc. Here is the output I get when trying to compile: ld -shared -o eda.so line.o smooth.o ld: Warning: Unresolved: floor ceil rsort __exc_add_pc_range_table __exc_add_gp_range __exc_remove_pc_range_table __exc_remove_gp_range make[4]: Leaving

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

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,

I tried to compile R-0.63.1 to R-0.63.3 on my DEC Alpha with the operating system of UNIX 4.0. All have the same problem after R.binary has been successfully compiled. The last few lines of the message are shown as below: ... make[4]: Entering directory `/home/ming/R-0.63.3/src/library/modreg/src' f77 -c bsplvd.f -o bsplvd.o f77 -c bvalue.f -o bvalue.o f77 -c bvalus.f -o bvalus.o f77

Dear R-help, I have encountered some errors when trying to compile R-1.3.1 from source on my WinNT4SP6 laptop (PII w/128MB RAM). I have installed all the tools following the instruction in src/gnuwin32/INSTALL, with the exception that the mingw compiler I have might be a bit older (they are the ones recommended for R-1.3.0, I believe). I have also compiled the ATLAS libraries from source using

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

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,

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

Greetings, I'm attempting to install R-0.64.1 on a Sun Sparc 20 running Solaris 2.4 with gcc-2.7.2.2, g77-0.5.20 and Gnu make 3.76-1. On several occasions, the make process aborted when trying to build the shared object file for the modreg package (its first attempt at such a beast). In all attempts, the error message is as follows: ../../../../bin/R SHLIB -o modreg.so bsplvd.o bvalue.o

Hello, Just a quick question about ppr in library modreg. I have looked at Ripley and Venables 2002 and it says that projection pursuit works "by projecting X in M carefully chosen directions" I want to know how it choses the directions? I presume it moves around the high-dimensional space of unit vectors finding ones that separate the response variables, but how. I looked at the

Dear R listers -- I have several questions about using the ppr command in the modreg module. I discovered -- quite by accident -- that if I re-order the data, I obtain different results. The output below shows what I mean. I have two datasets (dataset1 and dataset2) that are identical (tested using proc compare in SAS) except for the fact that the records are in different order. Below I have

Hi, if make and gmake are different on any machine (for example Solaris with gnu make as gmake), then compiling fails with gmake. A small transcript follows. If i make a link from gmake to make as under linux, then it works. This problem exists in all versions of R. g77 -O2 -fPIC -c sslvrg.f -o sslvrg.o g77 -O2 -fPIC -c stxwx.f -o stxwx.o ../../../../bin/R SHLIB -o modreg.so bsplvd.o bvalue.o

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

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

Dear list, yet another question on S4 method behaviour or rather its side effects: Consider the following example (see below) where a new S4 method 'predict' is defined which by doing so makes 'predict' a S4 standardGeneric. It works and simple test examples run but I'm cautious whether this is a 'silly' thing to do. Is this a dangerous thing to do, already known to

Hi, I've noted that not all `predict' methods are hidden in the namespace: > methods("predict") [1] predict.ar* predict.Arima* [3] predict.arima0* predict.glm [5] predict.HoltWinters* predict.lm [7] predict.loess* predict.mlm [9] predict.nls* predict.poly [11] predict.ppr* predict.prcomp* [13]

Hello everybody, I'm a new user of R and I'm working right now with the ACE function from the acepack library. I Have a question: Is there a way to predict new responses using ACE? What I mean is doing something similar to the following code that uses PPR (Projection Pursuit Regression): library(MASS) x <- runif(20, 0, 1) xnew <- runif(2000, 0, 1) y <- sin(x) a <- ppr(x, y,