similar to: evaluation of discriminant functions+multivariate homoscedasticity

While I don't know anything about Box's M test, I googled around and found a Matlab M-file that computes it. Below is my straight-forward translation of the code, without knowing Matlab or the formula (and done in a few minutes). I hope this demonstrates one of Prof. Ripley's point: If you really want to shoot yourself in the foot, you can probably program R to do that for you. [BTW:

Hello, I have run a discriminant analysis (with lda() from the MASS package) but I can't find a way to examine the p-values for the discriminant functions. I would like to calculate a Wilk's lambda and then the Bartlett's V statistic which is distributed as a chi squared and test its significance, but I haven't found out how to do so. Can anyone help? Thank you, Janke ten

Dear list, I would like to produce a matrix of plots, where par() is reset after each plot (see below [simplified] example). When I use layout() to do so, I seem to also reset the layout. I have not been able to figure out how to prevent this from happening. Any help is greatly appreciated! Janke Example code: #Desired result is a layout of 2 plots: one red and one black layout(matrix(1:2,

Hi R-programmers, I can't find find the White test to check the homoscedasticity of the residuals from a linear model. Could you please help me with this? Thank you ! BC [[alternative HTML version deleted]]

Hi r-programmers, I performe Breusch-Pagan tests (bptest in package lmtest) to check the homoscedasticity of the residuals from a linear model and I carry out carry out White's test via bptest (formula, ~ x * z + I(x^2) + I(z^2)) include all regressors and the squares/cross-products in the auxiliary regression. But what can I do if I want find coefficient and p-values of variables x, z, x*z,

Hello, Does logistic regression really provide better results than lda or qda ? (my purpose is not classification but highlighting of discriminant variables). If this is true, where could I get an R script performing stepwise logistic regression ? Thanks -- Daniel AMORESE Lab. M2C "Morphodynamique Continentale et C?ti?re" UMR CNRS 6143 Caen/Rouen Centre de G?omorphologie UCBN

Hi, I'm a newbie in R and don't much aobut all the modules and their capabilities, but I'm interested in solving a problem about a discriminant analysis done with SPSS tool. The thing is that I would like to make a discrimant analysis similar to the one done with SPSS, but I can't find the way to solve it. I've been playing with R and I can handle more or less my data,

Hello, I might have missed it in the help pages, but I cannot find if something exits in a package to make discriminant analysis. Any help, or hint about where to look for it, is welcome, Laurent -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help",

Can one perform a QDA in R? I do not see it anywhere within the mda package. Any pointers here would be appreciated. Thanks, cjf -- ~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~* Christopher J. Fonnesbeck Ph.D. Student Georgia Cooperative Wildlife Unit University of Georgia Athens, GA 30602 Email: cjf at fonnesbeck.net Yahoo: fonnesbeck_chris ~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*

Dear R Help Members, I am aware how to plot the LD1 vs LD2 from a lda in R, using the code: plot(baseline.systat.hat$x, col=baseline.systat.hat$class,pch=as.numeric(baseline.systat.hat$class)) However, I need to use the quadratic discriminant function, qda due to data properties. Is there a way to obtain the same sort of plot for from a qda object (and the output of predict qda). I have not

Are there any libraries in R that can do discriminant analysis? Lily Elloso Research Division Statistical Research and Training Center (SRTC) Quezon City, Philippines -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in

Hello list: (This is probably a stupid question).  Is there a "quick and easy" way to confirm the gauss-markov conditions of a linear multiple regression model?  That the mean of the residuals is 0 can easily be tested for. The normality of the residuals as well (shapiro-wilk?).  But what about homoscedasticity? And independence of residuals with respect to the model variables? Thanks

Dear R user, I'm using qda (quadratic discriminant analysis) function (package MASS) to classify 58 explanatory variables (numeric type with different ranges) using a grouping variable (factor 2 levels "0" "1"). I'm using the qda method for class 'data.frame' (in this way I don't need to specify a formula). Using the function:

Dear R gurus, Thank you all for continuous support and guidance -- learning without you would not be efficient. I have a question regarding LD analysis and how to best code it up in R. I have a file of (V52 and 671 time points across all columns) and another file of phonetic features (each vowel is aligned with a distinct binary sequence, i.e. E 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0

I have two regressions to perform - one with a metric DV (-3 to 3), the other with an ordered DV (0,1,2,3). Neither normal distribution not homoscedasticity is given. I have a two questions: (1) Some sources say robust regression take care of both lack of normal distribution and heteroscedasticity, while others say only of normal distribution. What is true? (2) Are there ways of using robust

Hello R people I now know how to run my discriminant analysis with the lda function in MASS: lda.alain=lda(Groupes ~ Ht.D0 + Lc.Dc + Ram + IDF, gr, CV = FALSE) and it works fine. But I am missing a test and cannot find any help on how to get it, if it exist. The "S" equivalent: discrim(structure(.Data = Groupes ~ Ht.D0 + Lc.Dc + Ram + IDF, class = "formula"), data = gr,

Hi listers, Does anybody knows if the function qda for quadratic discriminant analysis provides the coefficients of quadratic discriminants... Well, I find out that for the linear discriminant analysis lda, the fonction provides the coefficients... Thanks in advance, Marcio -- View this message in context: http://www.nabble.com/Quadratic-Discriminant-Analysis-%28qda%29-tp22747647p22747647.html

Perhaps, I should complement my previous e-mail question: I am trying to select variables through a quadratic discriminant analysis. It seems to me that a robust criterion is the value of the discriminatory power (i.e. the ratio of the separation of the class means to within-class variance) How can I obtain this ratio from V & R's qda() output ? Thanks (I hope this question is relevant) --

Hi, I have been using some of the functions in r for classification purposes, chiefly lda, qda, knn and nnet. My problem is that the only one I can figure out how to represenent graphically is lda (using plot.lda). I have tried 'fooling' this function into accepting qda input for plotting but to no avail. I wonder if you have any suggestions? Thanks alot, Anne Marie Power Marine lab.

Hi, I'm a R newbie and I have a supervised 2-class classification problem. To find out the best representation of my data (dim = 45). I want to perform LDA und QDA on the diffrent data representations to find out, which is best to discriminate the 2 sets. For LDA there exists a method plot.lda shows (in the 2 class case) a histogramm of the data, projected onto the linear discriminants (pleas