similar to: development mda package

I tried to convert hastie & tibshiranis mda package to R but ended with a bunch of unresolved symbols: R.binary: can't resolve symbol 'dbksl_' R.binary: can't resolve symbol 'dblepr_' R.binary: can't resolve symbol 'dqrdca_' R.binary: can't resolve symbol 'intpr_' R.binary: can't resolve symbol 'pack_' R.binary: can't resolve

I have just installed R 1.9.1 on an old Sun Sparc with the following specs: version Machine hardware: sun4u OS version: 5.6 Processor type: sparc Hardware: SUNW,Ultra-4 The following components are installed on your system: Sun Visual WorkShop C++ 3.0 Sun WorkShop Compiler C 4.2 Sun WorkShop Compiler C++ 4.2 Sun WorkShop Tools.h++ 7.0

{message bounced because it has "$$$" in it. manually approved by list maintainer -- MM} > Date: Tue, 22 Feb 2000 13:03:35 +0100 > From: jens <jniesch at gwdg.de> > > I have trouble to install R on Sparc Sun Solaris 2.6. > make returns the error message: > Undefined symbol first referenced in file > d_lg10 ../appl/libappl.a(uncmin.o) > d_sign

Dear helpers, I am trying to use the mda package downloaded from the R website, but the data set has missing values so I got an error message. Should I manually handle these missing values? I was trying to read the documents to specify any option related to missing values, but I did not find it. Please forgive me if I ignore something obvious. Thanks, Zhu Wang Statistical Science Department

Hello, I am new in R and I am delighted with it, so I am trying to bulid R-1.3.0 from sources under HP-UX 11.00 using f2c and X11 support. Configuration phase is OK but using make I have errors: gcc -Wl,-E -o R.bin CConverters.o Rdynload.o RNG.o apply.o arithmetic.o array.o attrib.o bind.o builtin.o charac ter.o coerce.o colors.o complex.o connections.o context.o cov.o cum.o dcf.o

Hello, I am new in R and I am delighted with it, so I am trying to bulid R-1.3.0 from sources under HP-UX 11.00 using f2c and X11 support. Configuration phase is OK but using make I have errors: gcc -Wl,-E -o R.bin CConverters.o Rdynload.o RNG.o apply.o arithmetic.o array.o attrib.o bind.o builtin.o charac ter.o coerce.o colors.o complex.o connections.o context.o cov.o cum.o dcf.o

Shuji, I suspect that bruto blows up because your data are linearly separable. To see this (if you didn't already know), try library(lattice) splom(~x, groups = y) and look at the first row. If you are trying to do classification, there are a few methods that would choke on this (logistic regression) and a few that won't (trees, svms etc). I would guess that bruto is in the latter

At 06:09 AM 5/1/00 +0100, Prof Brian D Ripley wrote: >On Sun, 30 Apr 2000, Stephen R. Laniel wrote: > >> I was just now surprised to note that functions to go generalized additive >> models don't appear to exist under R 1.000. In particular, the gam() and >> loess() functions aren't there. Are they hidden somewhere and I just >> haven't noticed? >

Dear R users, I'm trying to perform flexible discriminant analysis (fda) with method bruto. I applied the fda function on my training data: bruto.fda <- fda (fda.formula,data=train.data) where fda.formula is: PRES ~ VA_D123 + VA_D124 + VA_D127 + VA_DARU + VA_DCAN + VA_DFON + VA_DLAP + VA_DRID + VA_DRIR + VA_VVEG + VA_WDIN + VA_DIF3 + VA_DIF4 + VA_DIF5 + VA_CAAC + VA_CABC +

Hi, I''m currently thinking of writing my bachelorthesis about the use of model driven architecture within webdevelopment. I''m now trying to figure out about the benefits of using MDA to generate Rails Code. So, which Components of an Web-/Rails App would you like to be generated via MDA? In which way do you think the generators shipped with Rails can be improved? -- Posted via

Greetings everyone, I was wondering if anyone had experience in using fda (flexible discriminant analysis) in the mda package. Specifically, I can run the model but I cant locate/produce much of anything beyond the predicted values and confusion matrix. I've been searching for more examples or documentation but cant seem to locate any specific to the program itself. I need to be able to find

Hi all, Has anyone tried to do k-fold cross validation for flexible discriminant analysis ( mda library), for example, using crossval() in bootstrap? The problem is that the function crossval() requires a separate matrix for predictors and another for responses, whereas the function fda(), using the formula argument only. Is there another way of doing k-fold cross validation for functions which

Hello, I am using the function mda of the mda library in order to discriminate 4 groups with 8 explanatory variables. I only have 66 observations. I tested all possible combinations of those variable and run for each the Mixture Discriminant Analysis. For some iterations, I got an error message: "error in kmeans(xx, start): initial centers are not distinct". I understood that the

** High Priority ** I am a french student working on discriminant analysis issues. I am a new user of R language and have a few questions about its use : + About the mda package how can I plot the decision boundaries in the space of predictors from the results of the fda function ? + Does R include 3-D plots ? + How can I use bootstrap and cross-validation in classification ? I

I have recently noticed that some of our internal mailer scripts are causing Dovecot-LDA to generate Mailer Delivery Subsystem messages. The following Dovecot-LDA message is generated: ---- Message body ---- Your message was automatically rejected by Dovecot Mail Delivery Agent. The following reason was given: Unknown error ---- Message body ---- ---- Message header ---- Return-Path:

Hello all, So I'm doing some data analysis using MARS. I have a matrix of 65 independent variables, from which I'm trying to predict 71 dependent variables. I have 900+ data points (so a 900x136 matrix of data), which I randomly split into training and validation sets, for ~450 data points in each set. Occasionally, this works well, and I get decent predictions. However, quite often

Hi all, I'm at the stage of planning our new mail system and am evaluating dovecot for it. For large mailstore setups, it makes sense to split maildirs across many directories. I see that setting default_mail_env to something like maildir:/var/imap/domain/%1d/%d/%1u/user/%u/ would create almost identical on-disk layout as multidomain cyrus setup. Now, as dovecot does not have its own

For a private package ("soon" to be on CRAN), I started looking at and thinking about the function confusion() from the mda package and wondered if it wouldn't make sense to provide the generic function in base R and also think about making the default for the `true' argument equal to fitted(object). One could write methods for confusion() for almost all classifiers which

Hi, I am using function mars() in package mda to find knots in a whole bunch of predictor variables. I hope to be able to replicate all or some of the basis functions that the MARS software from Salford Systems creates. When I ran mars() on a small dataset, I was able to get the knots. However, when I tried running mars() on a larger dataset (145 predictor variables), for a different

Hello. First, I want to thank those responsible for Dovecot IMAP as it was a real treat to implement in comparison to my mostly-failed attempts with Cyrus. The passwd-file authentication was exactly what I needed as I really didn't want to have to deal with PAM or LDAP but where I am setting up a server with virtual accounts. I'm using Postfix as an MTA, and it quite handily passes