similar to: MASS package and lda

Hi, I've just upgraded to 1.9.0 and one of my Sweave files that produces a number of barplots in a standard manner now produces them in a different way. I have made a couple of small changes to my code to get the back the output I was getting before upgrading and now (mostly out of curiosity) would like to understand what has changed. I *think* I've tracked it down to tapply() and/or

Hello all, I'm trying to run lda() from the MASS library but the Help example generates the following error: #Code from example in lda Help file # Resulting Error >Error in if (targetlist[i] == stringname) { : argument is of length zero My Current R Installation: MacOSX: 10.5.8 R: 2.10.0 -- Gregory Riddick, PhD. CRTA Research Fellow National Institutes of Health National

Hi there, I am a master student in Denmark, and apply R to analyze the drug data. I use the function 'lda' to obtain a linear discriminant object, and then wish to use 'plot.lda' to do the plot on this object like below. drug.lda <- lda(Inhibition ~ NET_CHARGE + PKA_1 + MW + MLOGP, data = drug.class, method = "moment") plot.lda(drug.lda,

Hi R experts. I performed an Linear Discriminant Analysis (lda) and now I want to plot the first two axes (LDA1 and LDA2). Well MASS package have the plot.lda and pairs.lda to do that. But, they don’t let me personalize them, once they don’t accept the type=’n’ plot. So I start looking at the lda object properties, trying to found out my groups (n=4) axis coordinates, curiously I couldn’t. There

This question appears to have been asked previously, but not answered. the last response I can find to this previous thread is here: http://tolstoy.newcastle.edu.au/R/help/04/07/0126.html. The asnwer was to provide debugging info, not an answer. So the problem is that I'm trying to use lda on my dataset. You can download my data here: http://northstar-www.dartmouth.edu/~jgilbert/nolda, I used

I maintain the Irregular Time Series (its) package on CRAN. I am currently testing a release. Under 1.8.1 I am able to define a S4 generic 'start' as follows: if(!isGeneric("start")) {setGeneric("start", useAsDefault=start)} Under 1.9.0, Rcmd check generates an error, as 'start' is not recognised. If I use the NAMESPACE directive IMPORT, all is well:

Dear R Help team, I'm having some problems running a discriminant analysis (MASS:lda) over my data, i have a grouping variable coming from a previous cluster analysis and several discriminators (78 actually). I'm trying to run lda using column index as independent variable in the formula like it's done in the help page for ?formula:

hello list, when I use method lda of the MASS package I experience a warning: variables are collinear in: lda.default(data[train, ], classes[train]) Is there an easy way to recover from this issue within the MASS package? Or how can I tell how severe this issue is at all? I understand that I shouldn't use lda at all with collinear data and should use "quadratische" (squared?)

Hi all, I obtained a strage result with LDA (MASS) function in R with NIR data. I tried both CV (leave one out cross validation) and splitting my data in odd (training) and even (prediction) sets. In all the cases the minimum error was near to 0. Due to the strange result, I tried with SPSS IBM software and it give me around 11% of minimum error with and without leave one out cross validation.

Hello, I am using WinXP, R version 2.3.1, and SAS for PC version 8.1. I have mostly used SAS over the last 4 years and would like to compare the output of PROC DISCRIM to that of lda( ) with respect to a very specific aspect. My data have k=3 populations and there are 3 variates in the feature space. When using using the code PROC DISCRIM DATA = FOO OUT = FOO_OUT OUTSTAT = FOOSTAT

hi! this is a question about lda (MASS) in R on a particular dataset. I'm not a specialist about any of this but: First with the well-known "iris" dataset, I tried using lda to discriminate versicolor from the other to classes and I got approx. 70% of accuracy testing on train set. In iris, versicolor stands "between" the 2 other so one can expect lda not to perform well

Hello, Does the "lda" function (package MASS) perform or can it perform classic two-group Fisher discriminant analysis? R-version: 1.9.1, MASS package (latest available) Thank you, Borut Rajer

Hi, a colleague ran a stepwise discriminant analysis twice in a row and got different results, suggesting some "sochasticity" in the algorithms involved. I looked at her data and found that there was a lot of collinearity, so that I reckoned that maybe "stepclass" (klaR) cannot find a clear winner when trying to include a new variable and makes a random choice. Is that true?

Thanks David, Yes, I am talking about the MASS package.Thank you for pointing out that these scale the same. My question is, how do I get from the V1 data: V1 1 164.4283 2 166.2492 3 170.5232 4 156.5622 5 127.7540 6 136.7704 7 136.3436 to the other set of data: + 1 -2.3769280 + 2 -2.7049437 + 3 -3.4748309 + 4 -0.9599825 + 5 4.2293774 + 6 2.6052193 + 7 2.6820884 On Mon, Sep 28, 2009

Hi, it seems that the lda function in MASS library doesn''t give out the constant for the linear discriminant function under the situation that we don''t use standardized variable, anyone knows how to obtain the constant in order to construct the linear discriminant function? I understand that if the priors are set to be 1/2, the threshold of the discriminant score used to

Hi all, I am using the lda function from the MASS library to measure the discriminance of different variables with respect to different grouping variables by using lda( RESULTVARS[, 1:750] , GROUPVAR , tol=0 ) where RESULTVARS contains some 750 different variables. Occasionally there is a variable within RESULTVARS that has the same values for all values of GROUPVAR, ie no variance so

I'm seeking some advice on effectively using the new Matrix library in R1.9.0 for operations with large dense matrices. I'm working on integral operator models (implemented numerically via matrix operations) and except for the way entries are generated, the examples below really are representative of my problem sizes. My main concern is speed of large dense matrix multiplication. In R

Hi all, I just used power.t.test() in Version 1.9.0 beta (2004-03-31) today under FC1. The following is the output: > power.t.test(delta = .5, power = .95, type = "paired") $n [1] 53.94062 $delta [1] 0.5 $sd [1] 1 $sig.level [1] 0.05 $power [1] 0.95 $alternative [1] "two.sided" $note [1] "n is number of *pairs*, sd is std.dev. of *differences* within

Hi, I am using Partek for LDA analysis. For a binary response variable, it generates 2 discriminant functions, one for each of the 2 levels of the response variable. And I can simply calculate 2 discriminant scores (say d1 and d2) for each sampples using the 2 discriminant functions, then I can use the following formula to compute the posterior probability for the sample:

Hello all, I upgraded from R 1.8.1 to 1.9.0 (Windows XP), and spotted an odd thing. The last three letters in the Swedish alphabet are ??, ?? and ??. (In case they don't show correctly: they are a with a ring, a with two dots, and o with two dots (HTML: &aring; &auml; &ouml;). When I use these as variable names in a data.frame, odd things happen: In R 1.8.1, ?? (&aring;)