similar to: Stepwise Discriminant Analysis - greedy.wilks

I have used the greedy.wilks to stepwise discriminant analysis, but it doesn't work with my dataset. I don't understand which is the problem Could you help me please? Thanks in advance Marta > str(data_indiciN2) 'data.frame': 200 obs. of 36 variables: $ gruppo: Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 2 2 ... $ I001N2: num 19.32 8.22 28.35 7.24

Hello R list, I'm looking to do some stepwise discriminant function analysis (DFA) based on the minimization of Wilks' lambda in R to end up with a composite signature (of metals "Al","Sb","Bi","Cr","Ba") capable of discriminating 100% of the source factors (LANDUSE: "A","B","C"). The Wilks' lambda

Hello, R experts, Sorry for asking this question again again since I really want a help! I have a two-factor experiment data and like to calculate estimates of interation contrasts say factor A has levels of a1, a2, and B has levels of b1, b2, b3, b4, and b5 with 3 replicates. I am not sure the constrast estimate I got is right using the script below:

Dear all, It looks like the parameters var-cov matrix returned by gee() is not adjusted for the scale parameter: > fm1 <- gee(nbtrp ~ strate * saison + offset(log(surf)), family = poisson, data = Eff2001, + id = loc, tol = 1e-10, corstr = "exchangeable") [1] "Beginning Cgee S-function, @(#) geeformula.q 4.13 98/01/27" [1] "running glm to get initial

Hello, using the lda-method from MASS-package I was wondering whether there is a built-in method for figuring out Wilks' Lambda? Searching the Web I found in the r-help archive a thread form june 2002, but it didn't help me. I understand I can use manova and its summary-method to get Wilks' Lambda on the screen, but I don't see the connection to lda from MASS. Or does

Hello! As I remember there were questions concerning wilks' lambda lately. But I lost those e-mails. So I dare ask again. Is there a way of calculating wilks' lambda for lda? Christoph. -- Christoph Lange clange at epost.de Verhaltensbiologie, FU Berlin 838-55068 Haderslebener Str. 9, 12163 Berlin

Dear R-users, I'm wondering how to obtain Wilks-lambda values when discriminant analyses have only one discriminant function (i.e. 2 categories to discriminate between). The use of manova(predictions~groups, test="Wilks") asks for multiple response and the use of anova(lm(predictions~groups), test="Wilks") simply does not consider the last term. (The alternative

Hi all, I can't figure out how to compute Wilks Lambda in a one way repeated measure design. My matrix looks like: > t2.m Blank ECR ENC UEA UED 1 -0.15 0.14 0.16 0.09 0.14 2 0.30 0.08 0.14 0.14 0.14 [...] where each row is a case and the columns are levels of one factor (named trial): > t2.fit <- manova(t2.m ~ 1) > summary(t2.fit, intercept=T,

Hello, I have a question about multivariate Shapiro-Wilks test. I tried to analyze if the data I have are multivariate normal, or how far they are from being multivariate normal. However, any time I did >mshapiro.test(mydata) I get the message: Error in solve.default(R %*% t(R), tol = 1e-18) : system is computationally singular: reciprocal condition number = 5.38814e-021 I tried

Hi all, I am newbie in using R software and also doing statistical test. I want to know if my data in in normal distribution. I have 2 groups of data and I did calculate Shapiro Wilks using R software. Here is the results: Group 1: W = 0.9206, p-value = 0.01683 Group 2: W = 0.9626, p-value = 0.4694 I am not quite sure what default confidence level (CF) is used in calculating Shapiro Wilks.

Hi everybody, I was wondering if you can help me about a module. In fact, I'm looking for a package or module about Wilks' lambda criterion in R environment. I didn't find it in R website ( http://cran.cict.fr/web/packages/index.html#available-packages-W or http://search.cpan.org/faq.html). If this module exists, could you show me the command line. Thank you very much for your help,

Dear All, I would be very appreciative of your help with the following 1). I am running multivariate multiple regression through the manova() function (kindly suggested by Professor Venables) and getting two different answers for test=c("Wilks","Roy","Pillai") and tests=c("Wilks","Roy",'"Pillai") as shown below. In the

On Wed, Aug 1, 2012 at 3:08 PM, <fra.meucci@hotmail.it> wrote: > Dear Göran Broström, > I am trying to use AFTREG function for R to estimate a loglogistic > survival function, including time dependent covariates. > Actually, my Subset includes some partial events; the idea is to model > this kind of events using something similar to “weights” in the SURVREG > function.

Hi, there. Does anybody know how to plot a smooth density plot for some data simulated from certain distribution? Thanks. Yulei $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ Yulei He 1586 Murfin Ave. Apt 37 Ann Arbor, MI 48105-3135 yuleih at umich.edu 734-647-0305(H) 734-763-0421(O) 734-763-0427(O) 734-764-8263(fax) $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

Dear R users I get different F-statistic results for a "within" model, when using "time" or "twoways" effects in plm() [1] and when manually specifying the time control dummies [2]. [1] vignette("plm") [2] http://cran.r-project.org/doc/contrib/Farnsworth-EconometricsInR.pdf Two examples below: library("AER") data("Grunfeld", package =

Hello, R experts, I have a two-factor experiment data and like to calculate estimates of interation contrasts say factor A has levels of a1, a2, and B has levels of b1, b2, b3, b4, and b5 with 3 replicates. I am not sure the constrast estimate I got is right using the script below: score<-c(7.2,6.5,6.9,6.4,6.9,6.1,6.9,5.3,7.2,5.7,5.1,5.9,7.6,6.9,6.8,

Hello, R experts, Sorry for asking this question again since I really want a help! I have a two-factor experiment data and like to calculate estimates of interation contrasts say factor A has levels of a1, a2, and B has levels of b1, b2, b3, b4, and b5 with 3 replicates. I am not sure the constrast estimate I got is right using the script below:

Hello, R experts, Sorry for asking this question again since I really want a help! I have a two-factor experiment data and like to calculate estimates of interation contrasts say factor A has levels of a1, a2, and B has levels of b1, b2, b3, b4, and b5 with 3 replicates. I am not sure the constrast estimate I got is right using the script below:

I have two variables which show a typical quantile relation I would like to fit quantile regression models based on both logarithm and polynomial of second order functions within quantreg. Any help appreciated... Cheers Duccio Herewith the values: ------ var1 var2 0.96429 0.00138 1 0.02316 1.03145 0.09323 1.24088 0.77128 1.39869 0.86732 1.33728 0.63674 1.48299 0.96194

My operating system is Solaris 8 SPARC and it runs Samba 3.0.1 Any suggestions? I have included configuration/logs and traces. This is the smb.conf file: # Samba config file created using SWAT # from 151.184.34.182 (151.184.34.182) # Date: 2003/09/17 20:34:48 # Global parameters [global] netbios name = dali workgroup = DALIUNIX passdb backend = tdbsam os level