similar to: R/Chemometrics/reading .spa files into R.

This might be easy (but I didn't find an answer in the archives). I'm trying to make nice looking images (using image()). To make them look nice (not jagged), it usually takes me at least 100x100 points. This can be slow for frequent redraws. Is there a smarter (less point intensive) way? I was thinking in terms of hexabins, for example, which for much less jagged looking regions,

There is a little problem in handling logicals in RMySQL: # here is the MySQL connection > con <MySQLConnection:(1816,0)> # here is the data frame > print(a<-data.frame(x=c(TRUE,FALSE),y=c(FALSE,TRUE))) x y 1 TRUE FALSE 2 FALSE TRUE # as promised, the two data frame columns are identified as logicals and # the field types are set to tinyint > field.types <-

Hi to all who suffer from rterm not shutting down in xemacs/ESS on windows NT or 2000. Also hi to those who could eventually help. Here is some more information which could help and some ENCOURAGEMENT to contribute to a solution. 1. It may be an xemacs problem but it is more likely an interaction between rterm/comint/and xemacs. In fact, the problem started occurring around version R 1.6.0. I

(R 1.9.1; Windows 2000;) I'm just comparing ease of use, speed, etc for methods of transferring data frames in the Excel, MySQL, R triangle. It turns out that going from Excel to R (when doing this carefully). Using the clipboard is actually quite fast and efficient (2 seconds for transferring 120 000 cells on a common desktop computer as compared to much longer for going the RODBC route,

This problem is not limited to R, but R is one of the packages in which it arises. princomp is a nice function which creates an object for which inspection methods have been written. Unfortunately, princomp does not admit cases in which the x matrix is wider than high (i. e. more variables than observations). Such cases are typical in spectroscopy and related disciplines. It would be nice if the

Has anyone seen an official announcement to DSC-2005. I saw and email exchange on the R-news list in mid January in which a date was announced unofficially. (to DSC-organizers: we need and "official" announcement to request funding and travel permission and flights from Europe to Seattle are starting to fill up, so this is urgent). Christian Ritter Functional Specialist Statistics Shell

For some time now I use a modified version of names (extract direction) of the following type: Names<- function (x,filter="^") { grep(filter,names(x),value=TRUE) } Request: Has anyone already written a version which goes the other way (that is, which allows assignment of the type Names(x,filter)<-...). Naive versions are obvious, but I think something would have to be done

Hi all, Has any of you implemented code for non-negative matrix factorization to solve Y=T P' +E; dim(Y)=n,p ; dim(T)=n,nc; dim (P)=(p,nc); dim(E)=n,p where T and P must be non-negative and E either Gaussian or Poisson noise. I'm looking for two variants: 1. Easy (I think), T is known (that is we just want to solve the general inverse problem) 2. Harder (?), T is unknown (under some

R-2.1.1 on windows XP I just noticed something unpleasant when using bwplot (from lattice). In order to satisfy a wish from a client, I needed to produce sets of boxplots conditioned by another factor. My client didn't like the look of the boxplots (by default, they have a star to mark the median, instead of the commonly used line). I told him "no problem" dumped panel.bwplot,

... finding myself doing this by hand one too many times ... maybe someone else has found a nice general solution ... I have a data frame containing n rows on p+q variables which I will call p.1, p2, ..., pp and q1, q2, ... qq. For simplicity all of these variables are continuous numeric. I want to create the following arrangement of plots: A scatterplot matrix which contains p times q panels

After having browsed the documentation for a while without discovering what I am looking for, maybe one of you would know ... What I want to do: I have two fortran files MC.f and ESCA.f. In MC.f there is a call to a routine called lpost. This routine (lpost) is defined (among other things) in ESCA.f. Under linux, I can do the following: R CMD SHLIB MC.f and R CMD SHLIB ESCA.f followed by

Hi all, I''m still not quite happy with the NA and factor handling of lm and predict.lm in R1.6.1 (forcing me to use my not very skillfully crafted patches). Here is the problem 1: >

Hi all, I'll have to filter Raman spectra and I would like to do so in R. I'm trying to figure out how. Maybe one of you could help me ... This is what I have to do: General: separate the real spectrum (the set of peaks) from two contaminations: a drifting background and (white) noise Constraints (which should help the task): A - the spectrum is positive B - the spectrum is long

This message is for people who know the mechanics of model.frame within lm. I am fitting lm models for different responses on a data frame which has (at least some) factors. As it happens, some of the responses are NA for some of the factor levels. Logically, lm creates an xlevels list for which the length of levels is different from the original number of levels in the data frame (a

Here is the first one. It concerns the handling of multiple offsets. The following lines creates a list with 3 explanatory variables and one response. > x<-seq(0,1,length=10);y<-sin(x);z<-cos(x); w<-x+y+z+rnorm(x) > data<-list(x=x,y=y,z=z,w=w) A lm is fitted with one explanatory variable and two offsets. So far, so good. >

Dear friends, I'm confused about how to install packages from source. I just updated R in Lenny from http://cran.fiocruz.br/bin/linux/debian/ I included in sources.list: deb http://cran.fiocruz.br/bin/linux/debian lenny-cran/ deb-src http://cran.fiocruz.br/bin/linux/debian lenny-cran/ Then: apt-get update apt-get install r-base r-base-dev Then I downloaded the package

Hello i need some precision about nipals in the chemometrics package in R . When i use nipals in chemometrics i obtain T and P matrix. I really don't understand what to do with these two matrix to obtain the scores for every the component (like in spss fo example) Comp1 Comp2 Comp3 quest1 0,8434 0,54333 0,3466 quest2 0,665 0,7655 0,433 Thank you very

Dear All, A new task view "ChemPhys" on chemometrics and computational physics is available on CRAN (http://cran.r-project.org/web/views/ChemPhys.html). It describes packages and functions that are of use in modeling chemical/physical systems. Suggestions and comments regarding this task view are welcome. If you think a new category, package or function should be added, please mail.

... I checked and Brian and I are both right (see bottom for prior mail exchange). Let me explain: ============================================================= 1. Indeed, in principle, princomp allows data matrices with are wider than high. Example: > x1 [,1] [,2] [,3] [,4] [1,] 1 1 2 2 [2,] 1 1 2 2 > princomp(x1) Call: princomp(x = x1) Standard deviations:

... I checked and Brian and I are both right (see bottom for prior mail exchange). Let me explain: ============================================================= 1. Indeed, in principle, princomp allows data matrices with are wider than high. Example: > x1 [,1] [,2] [,3] [,4] [1,] 1 1 2 2 [2,] 1 1 2 2 > princomp(x1) Call: princomp(x = x1) Standard deviations: