similar to: discriminate analysis

Hello, I would like to use by to create a series of plots, but I'm not sure how to design the function. Here's what I've got: 1. A data frame of observations of measured value 2 measured vlaues and a pch code. V1 V2 pchCode .0045 123 1 .0034 145 2 .0045 123 1 .0046 167 3 ... So what I want to do is create a single scatterplot of the multiple conditions (specified by

Hello, Can anyone offer any insight on graphing classification dendrograms with the nodes marked? plot(tree()) produces a nice tree structure but there's no acccompanying text. Thanks, D S. David White sdavidwhite at bigfoot.com Columbus, Ohio -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

If so, I''ve had trouble finding it. Can anyone help?

Here's a nasty one. The following has caused a segmentation fault and possibly also a bus error. fred <- 1:6 dim(fred) <- 6 dimnames(fred) <- list(LETTERS[1:6]) mm <- matrix(1:12, 2, 6) mm %*% fred # segmentation fault here In the case without the dimnames assignment the result is OK. Cheers, Jonathan. --please do not edit the information below-- Version: platform =

Please, I would like to know how to generate a truncated multivariate normal distribution k - dimensional, X ~ NT(mu, Sigma), where the elements of X to be non-negative (except the first), and the first dimension is strictly larger than zero. Example: X ~ NT_2(mu, Sigma), where mu=c(0.5, 0.5) and Sigma=c([120, 191], [191,154]), with X_1>0 and X_2>=0 Could anybody help

Dear all, I have the following output generated by linear regression. Since there is only one regression intercept and one slope for one set of data, what is the meaning of std. error for intercept and that of slope? Thanks in advance. Sincerely, Minghua > data(thuesen) > attach(thuesen) > lm(short.velocity~blood.glucose) Call: lm(formula = short.velocity ~ blood.glucose)

Dear RHelpers, Does anyone know of any R code to perform bivariate Poisson regression (including random effects)? Best wishes Simon Simon D.W. Frost, M.A., D.Phil. Department of Pathology University of California, San Diego Antiviral Research Center (Formerly: UCSD Treatment Center) 150 W. Washington St., Suite 100 San Diego, CA 92103 USA Tel: +1 619 543 8080 x275 Fax: +1 619 298 0177 Email:

Hi all, I'm building a plot of the values in tmeant (below) against positions 1 to 5, using matplot. tmeant looks like this: case1 case2 pos1 861.8466 818.5909 pos2 961.2841 976.3466 pos3 878.6080 1262.8523 pos4 950.8011 1129.6080 pos5 968.1080 1063.3920 I also have lower (object tl) and upper (object tu) bounds on the confidence intervals as follows: tl: pos1

Dear R-help, Can some one tell me how to do the following (if it's possible)? Suppose I have a function like this: f <- function(x, y, ...) { ## some code g(x, y, ...) ## some more code } The problem is that g() may not understand everything that comes through in "...". Is there a way to delete some component of "..." and then pass it to g()? Here's

R help list subscribers, I am a new user of R. I am attempting to use R to explore a set of equations specifying the dynamics of a three trophic level food chain. I have put together this code for the function that is to be evaluted by LSODA. My equations Rprime, Cprime, and Pprime are meant to describe the actual equation of the derivative. When I run LSODA, I do not get the output that

Hello all, I've got a bunch of objects I'd like to write to .csv files. For example, I have objects conveniently called n002.csv n001.csv p103.csv . . . I tried a loop: > for(i in ls(pattern="csv")) +write.table(i, file=i, sep=",", quote=F) That, of course, wrote out a bunch of files that contained x 1, n002.csv Or the like. How can I get i in the loop above

I have a general style question about R coding. Suppose I'm writing a function (foo1) that calls other functions (foo2, foo3, ...) which have complicated argument lists (e.g. optim(), plot()), _and_ I may be calling several different functions in the body of foo1. Since foo2 and foo3 have different sets of arguments, I can't just use "..." ; I did write some code a while ago

Hi ! I've used the example given in the documentation for the prcomp function both in R and SPAD to compare the results obtained. Surprisingly, I do not obtain the same results for the coordinates of the principal composantes with these two softwares. using USArrests data I obtain with R : > summary(prcomp(USArrests)) Importance of components: PC1 PC2

I have two CSV files (exported from Excel), say file1 and file2. The have the same number of rows, and each has several columns, with names on the first line; and some of the columns in file1 are repeated in file2. Using the "foreign" package, I can read these in separately to dataframes say d1 and d2 with > d1<-read.csv("file1") >

Dear all, I found that the new feature of the comment.char="#" argument in the read.table function truncated my data while the data set actually contains '#'. We analyze lot of data that contain '#'. This is really annoying and it is also not compatible earlier version of R. I searched the R archive and found the following message for the scan function. Is it

Dear R-experts I would like to read all files from a directory, the files have names "myname0001.txt" etc. I paste the directory plus file names and use "read.delim()". My problem is that some file names are missing, so I get an error and my program stops. Is there a way to check for a null pointer analogous to C, so that I can simply skip non-existent filenames? Please do

How do I add error bars to an interaction plot of means? Thanks

Hey, all I am going to plot several 3-dimensional ellipsoids in R. For example, A is such a ellipsoid with mean u=[1 1 1]', covariance matrix C=[1 0 .5;0 1 .6;.5 .6 1]; So how can I plot such object in 3D space? Is there some function to achieve this? Thanks. Fred

I'm trying to get a grasp of maximum-likelihood estimation and would like to find a package that performs mle (hopefully a simple example). It seems as if there are plenty of packages that make use of different types of likelihood estimators, but none are of a simple, "newbie" type. Does anyone have a suggestion for which package would be the best for a mle example? Thanks, Jeff.

I'm probably missing something very basic here, but: I've written some C code that I load into R dynamically. In the course of this C code, I generate some multinomial random deviates. I initially used the publically available "randlib" library, which also implements its own random number generator and binomial deviates (which are used to generate the multinomial deviates).