similar to: PB Mandeville can't be reached

I am having a problem understanding the lda package. I have a dataset here: [,1] [,2] [,3] [1,] 2.95 6.63 0 [2,] 2.53 7.79 0 [3,] 3.57 5.65 0 [4,] 3.16 5.47 0 [5,] 2.58 4.46 1 [6,] 2.16 6.22 1 [7,] 3.27 3.52 1 If I do the following; "names(d)<-c("y","x1","x2") d$x1 = d$x1 * 100 d$x2 = d$x2 * 100 g<-lda( y ~ x1 + x2, data=d) v2

Hi, I run this code to get the power of the test for modified bartlett's test..but I'm not really sure that my coding is right.. #normal distribution unequal variance asim<-5000 pv<-rep(NA,asim) for(i in 1:asim) {print(i) set.seed(i) n1<-20 n2<-20 n3<-20 mu<-0 sd1<-sqrt(25) sd2<-sqrt(50) sd3<-sqrt(100) g1<-rnorm(n1,mu,sd1) g2<-rnorm(n2,mu,sd2)

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

Hello there, I have two data sets with 14 variables each, and wish to do the test for equality of their covariance matrices and mean vectors. Normally these tests should be done by chi square test (box provided) and Hotelling's T square test respectively. Which R functions could do this kind of test? I just find some functions could do for one dimension, but no for multidimension. Some one

I would like to test the hypothesis that the difference between pairs, for several variables, is zero. This is easily done separately for each variable with: lm(Y ~ rep(0, nrow(Y))) where Y is a matrix whose columns are the differences for each variable between pair members. However, I would like to get an overall probability across all variables from a Wilks or Pillai-Bartlett statistic as in

By accident, I left out the lines defining n1 and n2. Here it is as a function. Peter B. hotelling <- function(d1,d2){ k <- ncol(d1) n1 <- nrow(d1) n2 <- nrow(d2) xbar1 <- apply(d1,2,mean) xbar2 <- apply(d2,2,mean) dbar <- xbar2-xbar1 v <- ((n1-1)*var(d1)+(n2-1)*var(d2))/(n1+n2-2) t2 <- n1*n2*dbar%*%solve(v)%*%dbar/(n1+n2) f <-

Dear R/S users; I'm using S+ version 4 Release 3. and I am trying to do a simple calculation like the following : > X1<-X[1:5] > W1<-W[1:5,1:5] > X1 [1] 1.250000 1.292308 1.176471 0.937500 1.538462 > W1 VAR00003 VAR00004 VAR00005 VAR00006 VAR00007 1 0 1 0 1 0 2 1 0 0 0 1 3 0 0 0

Hi All, I am trying to reproduce this using R instead. [image: Full-size image (38 K)] I tried using the following code *SChla <- read.csv("SM_Chla_data.csv")* *Atlantis <- SChla[16:66,]* *head(Atlantis)* * * Seamount Station Depth Pico Nano Micro Total_Ch dbar Latitude Longitud 16 Atlantis 1217 Surface 0.0639 0.1560 0.0398 0.2597 2.082 -32.71450 57.29733

I'm having issues when trying to do a filled State plot using the maps() package. It seems that the color values aren't being plotted correctly, and I'm not sure why... I've started debugging it, but I'm stuck. I've attached the code that I've got so far. The for loop plots states 1:i. What I'm noticing is that the colors are correct until after Michigan gets

I've been attempting to understand the one-sample run test for randomness. I've found run.test{tseries} and run.test{lawstat}. Both use a large sample approximation for distribution of the total number of runs in a sample of n1 observations of one type and n2 observations of another type. I've been unable to find R code to generate the exact distribution and would like to see how

R-help, I have the following file I want to import to R (some lines removed) Calibrated CTD data for station:00280001 Calibrated:23/8 2001, Salinity Unsmoothed, Fluorescence Uncalibrated Maximum observed depth: 36 m QUAL has one digit for each of pressure, temp., sal. and fluor. QUAL=1:Uncal., QUAL=2:OK, QUAL=6:Interp., QUAL=9:No data

Dear All, I am running a simulation to obtain coverage probability of Wald type confidence intervals for my parameter d in a function of two parameters (mu,d). I am optimizing it using "optim" method "L-BFGS-B" to obtain MLE. As, I want to invert the Hessian matrix to get Standard errors of the two parameter estimates. However, my Hessian matrix at times becomes

This is a proposal for either adding a new, or updating an existing command line option such that a diagnostic can optionally be produced for unused -D macros. Long-lived large projects with thousands of files and many contributors have a tendency to accumulate build options over time. As time passes some build options like macros become replaced, obsolete, or simply no longer used. At the same

R 1.8.0 on Windows XP Professional. A huge THANK YOU to the R Team for this marvelous software. I am making lattice plots of oceanographic data. The usual layout does not conform to plotting conventions that marine scientists use when depth is the independent variable. Under those conventions, plots are made with the origin at the upper left, depth on the vertical axis (increasing as it

I want to calculate the probability that a group will include a particular point using the squared Mahalanobis distance to the centroid. I understand that the squared Mahalanobis distance is distributed as chi-squared but that for a small number of random samples from a multivariate normal population the Hotellings T2 (T squared) distribution should be used. I cannot find a function for

I am doing a cluster analysis with hclust. I want to get hclust to output the Hotelling's T squared statistic for each cluster so I can evaluate is data points should be in a cluster or not. My research to answer this question has been unsuccessful. Does anyone know how to get hclust to output the Hotelling's T squared statistic for each cluster? Mike [[alternative HTML version

I am adding -D k=v to yaml2obj, similar to clang -D. This makes it easy to generate {32-bit,64-bit} x {big-endian,little-endian} tests. --- !ELF FileHeader: Class: ELFCLASS[[BITS]] Data: ELFDATA2[[ENCODE]] Type: ET_DYN Machine: EM_X86_64 # RUN: yaml2obj -D BITS=32 -D ENCODE=LSB %s -o %t.32le # RUN: yaml2obj -D BITS=32 -D ENCODE=MSB %s -o %t.32le # RUN: yaml2obj

?The idea itself is indeed good. Regarding to escaping: I think we should have it. Imagine the following example (I've took it from D73828). --- !ELF FileHeader: Class: ELFCLASS[[BITS]] Data: ELFDATA2LSB Type: ET_EXEC Machine: EM_386 # RUN: yaml2obj %s --docnum=4 -D BITS=32 -o %t-32bit.o # RUN: yaml2obj %s --docnum=4 -D BITS=64 -o %t-64bit.o Without escaping it would

Hi all, I have a user login form which the browser keeps populating because of its form fill feature. So when anyone goes to log in it shows the previous login''s username and password. How can I stop the browser from populating a text field? Thanks in advance. Cheers, Diego --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to

Hi, I want to do a 2 sample hotelling's test but i can't figure out how. When i type T2.test it says there is no such test and when i tried library(rrcov) it says there is no such program. Cheers. -- View this message in context: http://r.789695.n4.nabble.com/How-to-do-Hotelling-s-t2-test-tp4128748p4128748.html Sent from the R help mailing list archive at Nabble.com.