similar to: discriminant analysis

Hi, I would like to conduct a MANOVA. I know that there 's the manova() funciton and the summary.manova() function to get the appropriate summary of test statistics. I just don't manage to specify my model in the manova() call. How to specify a model with multiple responses and one explanatory factor? If I type:

Dear colleagues, I've been searching for information on the Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy (MSA). This statistic is generated in SPSS and is often used to determine if a dataset is "appropriate" for factor analysis -- it's true utility seems quite low, but it seems to come up in stats classes a lot. It did in mine, and a glance through the R-help

Hi All, How do i calculate KMO for a dataset? *Dataset:---------------------* m1 m2 m3 m4 m5 m6 m7 m8 1 2 20 20 2 1 4 14 12 2 9 16 3 5 2 5 5 15 3 18 18 18 13 17 9 2 4 4 7 7 2 12 2 11 11 11 5 7 8 5 19 5 2 20 18 6 7 4 7 4 7 9 3 3 7 5 5 5 12 5 13 13 12 8 6 6 4 3 5 17 17 16 9 12 12 4 2 4 4 14 14 10 5 14

Hej! I have the following problem: I would like to do partial correlations on non-parametric data. I checked "pcor" (Computes the partial correlation between two variables given a set of other variables) but I do not know how to change to a Spearman Rank Correlation method [pcor(c("BCDNA","ImProd","A365"),var(PCor))] Here''s a glimpse of

Hi All, This is my R-version information:--- > version _ platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 7.1 year 2008 month 06 day 23 svn rev 45970 language R version.string R version 2.7.1 (2008-06-23) While calculating partial

I'm trying to write code to calculate partial correlations (along with p-values). I'm new to R, and I don't know how to do this. I have searched and come across different functions, but I haven't been able to get any of them to work (for example, pcor and pcor.test from the ggm package). In the following example, I am trying to compute the correlation between x and y, while

Dear all, I'm writing my manuscript to publish after analysis my final data with ANOVA, ANCOVA, MANCOVA. In a section of my result, I did correlation of my data (2 categirical factors with 2 levels: Quantity & Quality; 2 dependent var: Irid.area & Casa.PC1, and 1 co-var: SL). But as some traits (here Irid.area) are significantly influenced by the covariate (standard length, SL), I

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

Muy buenas, quiero calcular correlaciones de Pearson entre dos variables (a,b) teniendo en cuenta una tercera (c). Para ello estoy usando una función llamada "pcor.test" (http://www.yilab.gatech.edu/pcor.html), que en realidad no está en ningún paquete de R, que yo sepa. ¿Alguien conoce una función similar en alguna librería de R? Por otro lado, para ver si me cuadraban los resultados,

Hello everyone My name is Vangelis and I want to ask a question about partial correlation. I have used the command "pcor.shrink" to evaluate the partial correlations of a data.frame but the problem is that in the output results I cannot see whether these correlations are significant or not. Is there any command which can show me if these correlations are significant at 95% level or

Hi, I am using the lda function from the MASS library. I would to find the decision boundaries of each class and subsequently plot them. I wonder if anybody can offer any help on this topic? Below I applied the lda function on a small dataset of mine. Any help will be much appreciated. > library(MASS) >

I get this error while computing partial correlation. *Error in solve.default(Szz) : system is computationally singular: reciprocal condition number = 4.90109e-18* Why is it?Can anyone give me some idea ,how do i get rid it it? This is the function i use for calculating partial correlation. pcor.mat <- function(x,y,z,method="p",na.rm=T){ x <- c(x) y <- c(y)

Hello everyone I tried to install the library GeneNT in order to use the command pcor.confint because I want to construct confidence intervals for partial correlations but among other demanding the specific library needs the library "Graph" which I don't have it and I cannot find it at this site. Is there any other site that I can download this library? Thanks Kind regards

Hello, I'm looking for an efficient function for calculating partial correlations. I'm currently using the pcor.test () function, which is equivalent to the cor.test() function, and can receive only single vectors as input. I'm looking for something which is equivalent to the cor() function, and can receive matrixes as input (which should make the calculations much more efficient).

---------- Forwarded message ---------- From: <r-help-bounces@r-project.org> Date: Mon, May 11, 2009 at 10:24 PM Subject: The results of your email commands To: das.moumita.online@gmail.com The results of your email command are provided below. Attached is your original message. - Results: Ignoring non-text/plain MIME parts - Unprocessed: What is the function for partial

Why do we get Partial correlation values greater than 1? I have used the default function pcor.mat :-- I have manipulated the default pcor.mat function a bit so ignore tha variables corr_type,element1_in_no,element2_in_no,P.Please ignore the ?pairwise? section and have a look at athe ?listwise ? part i.e else part. *pcor.mat <-

r-help: I have an R package suggestion. After spending several hours the other day installing about a dozen packages, I had an idea. In xemacs, there is a "sumo" package which allows me to install a large bundle of xemacs packages at one time (about a 120 modes including ESS). I think R should have a similar bundle. It would be so much easier than hunting/downloading/installing.

Dear list, I have to look examine hourly time - series and would like to plot variable section of them using plot.zoo. Hourly time series data which looks like this: YYYY MM DD HH P-uk P-kor P-SME EPOT EREA RO R1 R2 RGES S-SNO SI SSM SUZ SLZ 2003 1 1 1 0.385 0.456 0.021 0.000 0.000 0.000 0.013 0.223 0.235 0.01 0.38

It does appear the ess package on CRAN for Ubuntu 8.04 fails to install the file 'ess-sas-sh-command'. This prevents invoking SAS via 'M-x SAS'. http://cran.mirrors.hoobly.com/bin/linux/ubuntu/README.html --Dale On Fri, Jul 11, 2008 at 12:39 PM, Rodney Sparapani <rsparapa at mcw.edu> wrote: > Dale Steele wrote: >> >> I re-installed from Hardy packages on

Hello, after thorough searching of the R help files as well as S+-help, I'm coming to the list: Is there a possibility to compute partial correlation coefficients between multiple variables (correlation between two paired samples with the "effects of all other variables partialled out")? All I seem to find are the standard Pearson correlation coefficients (with cor()) and no clue