search for: admitted

I apologize in advance if this is the wrong forum for this report/request, and for the fact that I have not read the code for ftable.formula in any detail. >From reading the documentation for ftable.formula, I expected that the following two calls to ftable would produce the same results: data(UCBAdmissions) ftable(UCBAdmissions, row.vars = "Dept", col.vars = c("Gender",

Dear all, The new version of AdMit (version 1.01-01) is now available from CRAN. SUMMARY The package provides functions to perform the fitting of an adaptive mixture of Student-t distributions to a target density through its kernel function. The mixture approximation can then be used as the importance density in importance sampling or as the candidate density in the Metropolis-Hastings

Dear all, The new version of AdMit (version 1.01-01) is now available from CRAN. SUMMARY The package provides functions to perform the fitting of an adaptive mixture of Student-t distributions to a target density through its kernel function. The mixture approximation can then be used as the importance density in importance sampling or as the candidate density in the Metropolis-Hastings

...ity is flattened to a 2D display, for example with ftable(), or vcd::structable, as shown below. I'd be happy to settle for a flexible solution for the 3D case. > UCB <- aperm(UCBAdmissions, c(2, 1, 3)) > ftable(UCB) Dept A B C D E F Gender Admit Male Admitted 512 353 120 138 53 22 Rejected 313 207 205 279 138 351 Female Admitted 89 17 202 131 94 24 Rejected 19 8 391 244 299 317 > structable(Dept ~ Admit+Gender, UCBAdmissions) Dept A B C D E F Admit Gender Admitted Male...

Dear List, I'm having problem with an exercise from The R book (M.J. Crawley) on page 567. Here is the entire code upto the point where I get an error. data(UCBAdmissions) x <- aperm(UCBAdmissions, c(2, 1, 3)) names(dimnames(x)) <- c("Sex", "Admit?", "Department") ftable(x) fourfoldplot(x, margin = 2) dept<-gl(6,4) sex<-gl(2,1,24)

Hi everyone, I am trying to build a table putting standard errors horizontally. I haven't been able to do it. library(memisc) berkeley <- aggregate(Table(Admit,Freq)~.,data=UCBAdmissions) berk0 <- glm(cbind(Admitted,Rejected)~1,data=berkeley,family="binomial") berk1 <- glm(cbind(Admitted,Rejected)~Gender,data=berkeley,family="binomial") berk2 <- glm(cbind(Admitted,Rejected)~Gender+Dept,data=berkeley,family="binomial") setCoefTemplate(est.se=c(est = "($est:#)($se:#)&q...

Hi everyone, I am trying to build a table putting standard errors horizontally. I haven't been able to do it. library(memisc) berkeley <- aggregate(Table(Admit,Freq)~.,data=UCBAdmissions) berk0 <- glm(cbind(Admitted,Rejected)~1,data=berkeley,family="binomial") berk1 <- glm(cbind(Admitted,Rejected)~Gender,data=berkeley,family="binomial") berk2 <- glm(cbind(Admitted,Rejected)~Gender+Dept,data=berkeley,family="binomial") setCoefTemplate(est.se=c(est = "($est:#)($se:#)&q...

I am trying to write the following code in R. The code works in S+ and i am trying to do the program in R. x=discrim(admit~gpa+gmat,prior=c("uniform"),data=data.mm) i wrote the following in R: x=lda(admit~gpa+gmat,data=data.mm) i could not figure out how to write prior=c("uniform") in R. I would get an error every time. I think that it has something to do with

Just a general question concerning the woolf test (package vcd), when we have stratified data (2x2 tables) and when the p.value of the woolf-test is below 0.05 then we assume that there is a heterogeneity and a common odds ratio cannot be computed? Does this mean that we have to try to add more stratification variables (stratify more) to make the woolf-test p.value insignificant? Also in the

'AdMit' 1.00-02 is a contributed R package which provides functions to perform the fitting of an adaptive mixture of Student-t distributions to a target density through its kernel function. The mixture approximation can then be used as the importance density in importance sampling or as the candidate density in the Metropolis-Hastings algorithm to obtain quantities of interest for the

...ponseName). This is the inverse of xtabs." For example, from ?xtabs, using the ?UCBAdmissions dataset, which is a 3 dimension table: > str(UCBAdmissions) table [1:2, 1:2, 1:6] 512 313 89 19 353 207 17 8 120 205 ... - attr(*, "dimnames")=List of 3 ..$ Admit : chr [1:2] "Admitted" "Rejected" ..$ Gender: chr [1:2] "Male" "Female" ..$ Dept : chr [1:6] "A" "B" "C" "D" ... DF <- as.data.frame(UCBAdmissions) > str(DF) 'data.frame': 24 obs. of 4 variables: $ Admit : Factor w/ 2 level...

...")), makeDimNames(attr(x, "col.vars"))), row.vars=NULL, col.vars=NULL) } Some test cases: > UCB <- UCBAdmissions > as.matrix(ftable(Dept ~ Admit + Gender, data=UCB)) Dept Admit_Gender A B C D E F Admitted_Male 512 353 120 138 53 22 Admitted_Female 89 17 202 131 94 24 Rejected_Male 313 207 205 279 138 351 Rejected_Female 19 8 391 244 299 317 > as.matrix(ftable(Dept ~ ., data=UCB)) Dept Admit_Gender A B C D E F Admitted_Male 512 353 120...

Hi, So, we currently have gc.result.int, gc.result.float. gc.result.ptr, gc.relocate, and gc.statepoint. gc.statepoint's signature is fine with a iPTRAny as the first argument. gc.result is in trouble, because none of the signatures admit even a simple array of integers, and there's no aAny. And certainly no vectors. So we can get a gc.result.vector to add to this mess, and admit [1] to

Hi All, What are my e-mail serving options? I need to host POP, IMAP and SMTP. I must admit that non-windows e-mail hosting has always been a chore for me. I remember QMail and QPopper IIRC. -Jason

Hello, Currently it's possible to convert an object of class table to a data frame with as.data.frame.table(), but there's no ready-made function, AFAIK, to do the reverse operation, i.e. conversion of a data frame to a table. Do you think it would be a good idea to add a data.frame method to as.table(), to allow such conversions? The idea is that if `x' is a table and `y <-

I would just like to give a success report, since this list gets mostly bugs and questions.. Due mainly to the help that this list provided, I am now able to successfully deploy Linux/Samba servers in our corporate domain, and allow remote offices to function as part of our vast windows domain. Things are working, and the $$$ it has saved us is almost unmeasurable. Again, thanks for your help,

Hi all, Could somebody be so kind to explain to me what is the saturated model on which deviance and degrees of freedom are calculated when fitting a binomial glm? Everything makes sense if I fit the model using as response a vector of proportions or a two-column matrix. But when the response is a factor and counts are specified via the "weights" argument, I am kind of lost as far as

Hi Neil, I admit that at this point I haven't considered the implications of the license MPFR is under, and at the moment I'm sticking my head in the sand until and unless we want to go down this path. My expectation is that we would use their exposed API - so we'd #include <mpfr.h> and use functions from there, linking against -lmpfr and -lgmp. I admit that this option would

Dear all, I admit this is not anything to do R and even with Statistics perhaps. Strictly speaking this is a math related question. However I have some reasonable feeling that experts here would come up with some elegant suggestion to my question. Here my question is: What is sum of all Integers? I somewhere heard that it is Zero as positive and negative integers will just cancel each other out.

On Mon, 2017-11-27 at 21:50 +0000, Rowland Penny wrote: > > Hi Andrew, > I think you understand what I have been saying for some time now, > upgrade from an NT4-style to AD before it is too late. > > However, are you ready yet to admit that Samba should mark NT domains > as deprecated ? I don't see it as admitting or otherwise, the Samba NT4 domain code remains a fully