similar to: help with lda function from MASS package

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

Hello, I have a question regarding the candisc package. My data are: species three five 1 2.95 6.63 1 2.53 7.79 1 3.57 5.65 1 3.16 5.47 2 2.58 4.46 2 2.16 6.22 2 3.27 3.52 I put these in a table and then a linear model >newdata <- lm(cbind(three, five) ~ species, data=rawdata) and then do a candisc on them >candata<-candisc(newdata)

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)

# Peter B. Mandeville kindly offered to send me code for Hotelling's T^2 # Test. Unfortunately there seems to be no route to his machine. # So i'm trying to reach him via the Mailing List. ------------------------------------------------------------------------ Sir, this morning i recieved your message about the availability of the code for Hotelling's Test. I hurried to find out

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

Dear R family, I faced a technical problem in r coding. #s=t(dev)%*%dev/(nr-1) # dev (100,000 by 2) stands for deviation from the mean #sinv=solve(s) #t2=diag(dev%*%sinv%*%t(dev)) I got an error message at t2 statement: Error in diag(dev %*% si %*% t(dev)) : allocMatrix: too many elements specified Please let me know if there is a way to overcome this problem. best moohwan

In one particular situation predict.coxph gives an error message. Namely: stratified data, predict='expected', new data, se=TRUE. I think I found the error but I'll leave that to you to decide. Thanks, Chris ######## CODE library(survival) set.seed(20121221) nn <- 10 # sample size in each group lambda0 <- 0.1 # event rate in group 0 lambda1 <- 0.2 # event rate in group 1

Hi I'm missing something here but I cannot figure out what. What I can see is that the same code works when I load it via source(...) yet fails when I execute it after loading the package I have built (which includes the code. Below is a transcript of my R session. First I load the code from a file, using source(). Then I execute it fine. Then I remove the function object, I load the

When building from git we need autoconf, automake and libtool. Signed-off-by: Nir Soffer <nsoffer at redhat.com> --- Changes sinve v1: - Remove `,` between package namses (Laszlo) README.md | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/README.md b/README.md index c7166613..7eed0e31 100644 --- a/README.md +++ b/README.md @@ -32,10 +32,17 @@ ## License very liberal license.

On 4/17/23 18:44, Nir Soffer wrote: > When building from git we need autoconf, automake and libtool. > > Signed-off-by: Nir Soffer <nsoffer at redhat.com> > --- > > Changes sinve v1: > - Remove `,` between package namses (Laszlo) > > README.md | 7 +++++++ > 1 file changed, 7 insertions(+) > > diff --git a/README.md b/README.md > index