similar to: conditions simpler way

Dear Users, I helped to install R Commander and FactoMineR to one of my collegaues. He wanted to do an MCA. Selecting three variables and using the default settings results in only one graph, the variables representation, where he gets three points for the three variables (which is totally fine). Running the code (output of the point-and-click method) EuTop100.MCA<-EuTop100[,

Dear all, suppose I have a vector with elements as: Vec <- c(2,3,4,5,6) Now I want to have all possible combination of length 3 using those elements and without any repetition. Like, I want to have 1 possibility like 2-3-4 but not 3-2-4. Can somebody guide me how to achieve that in R? Thanks for your help.

Dear Users, I installed R Commander and the FactoMineR plug-in. Everything is fine, I can see the new menu, I can import datasets, but if I want to use any of the items in the FactoMineR menu, i get the following error: Error in get(.activeDataSet) : object '.activeDataSet' not found even if there is an active dataset (if there is none, all the menu items are grey of course). I have R

Suppose I have a dataframe 'd' defined as L3 <- LETTERS[1:3] d0 <- data.frame(cbind(x = 1, y = 1:10), fac = sample(L3, 10, replace = TRUE)) (d <- d0[d0$fac %in% c('A', 'B'),]) x y fac 2 1 2 B 3 1 3 A 4 1 4 A 5 1 5 A 6 1 6 B 8 1 8 A Even though factor 'fac' in 'd' only has 2 levels, but it seems to bear the birthmark

Hi guys! I have to compute something and i don't know what i'm doing wrong. my code is a bit complex, but imagine that is something like this: a = c(1,2,3,4) ia = length(a) x = seq(1,100,length=0.1) ib = length(x) int1 = numeric(ib) b = numeric(ib) for(j in 1:ia) { H = function(x) {sin(x + a[j])} for(i in 1:ib) { int = integrate(H, lower = 0, upper

Hi guys! I have to compute something and i don't know what i'm doing wrong. my code is a bit complex, but imagine that is something like this: a = c(1 2 3 4) ia = length(a) x = seq(1,100,length=0.1) ib = length(x) for(j in 1:ia) { H = function(x) {sen(x) + a[j]} for(i in 1:ib) { int = function(x) { integrate(H, lower = 0, upper = x[i])} int1[i] = int(1) } end

Please start a new thread for a new topic and use a meaningful subject for sake of the archives and everyone trying to follow. Using your Int1, correcting your Int2 and using your Y (which goes to Jul not Aug as per the comment): library(zoo) > as.ts(with(merge.zoo(Int1, Int2, Y, fill = 0), pmax(Int1, Int2))) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1992

I am receiving the above error ( full r session output below) the script runs OK in windows. and "genotypes" and "ploidy" are both correct arguments any suggestions would be most welcome Nevil Amos MERG/ACB Monash University School of Biological Sciences > library(Geneland) Loading required package: RandomFields Loading required package: fields Loading required

Deal all, as MCMClogit does not allow for the specification of several chains, I have run my model 3 times with different random number seeds and differently dispersed multivariate normal priors. For example: res1 = MCMClogit(y~x,b0=0,B0=0.001,data=mydat, burnin=500, mcmc=5500, seed=1234, thin=5) res2 = MCMClogit(y~x,b0=1,B0=0.01,data=mydat, burnin=500, mcmc=5500, seed=5678, thin=5) res3 =

Hello, I would like to know if there is an instruction to convert values from the Int1 type to the Double type in LLVM. I would like to achieve the equivalent of casting a bool value to a double value in C++. Doing the simple CreateSIToFP or CreateUIToFP does not work, it throws an assertion ("invalid cast"). I simply want to avoid branching it's not necessary. What's the

Hi, I want to compute the bitwise 'and' between two values of type int1:  %x = and %a, %b  . Which is the LLVM instruction that creates this? I only found the APInt class, whose constructor is:  APInt(unsigned numBits, uint64_t val, bool isSigned = false) and which provides the bitwise AND operation: APInt  llvm::APIntOps::And (const APInt &LHS, const APInt &RHS)   Bitwise

Hello! I often plot average of y instead of all y values, since one can easily see the trend if there is to many points and/or x might be like 1, 2, 3, 4, 5, ... and you might get a cloud (which can also be informative) and/or columns of points. Anyway, learning with R i get stucked. I have the data in table burnins1, with the following names: names(burnins1) [1] "Model"

Dear Members, I have two estimated transition matrices and I want to compare them. In fact I want to check the hypothesis if they come from the same process. I tried to look for some test but all I found was independence test of contingency tables. The following code shows that the usual chi-squared test statistic does not follow chisq distribution. MCRepl <- 5000 khi12 <- rep(0,MCRepl)

Hi, I??m trying to use the Win2BUGS package from R and I have a similar problem that reurns with the message: Error in FUN(X[[1]], ...) : symbol print-name too long But, there is no stray ` character in the file ( Sugestions given by: Duncan Temple Lang <duncan> Date: Mon, 26 Sep 2005 07:31:08 -0700 ) The progam in R is: library(R2WinBUGS) library(rbugs) dat <-

Hi, A question. When I run gelman.diag and gelman.plot with mcmc lists obtained from MCMCregress, the results are following. > post.R <- MCMCregress(Size~Age+Status, data = data, burnin = 5000, mcmc = 100000, + thin = 10, verbose = FALSE, beta.start = NA, sigma2.start = NA, + b0 = 0, B0 = 0, nu = 0.001, delta = 0.001) > post1.R <- MCMCregress(Size~Age+Status, data

Hi all, Does anybody have a hint on what may be going wrong in this R code? I mimic the sample code from the MNP developers but I seem unable to get the choice specific variables right. Thanks, Joan Serra > rm(list=ls()) > library(foreign) > small<-read.spss("small.sav") Warning message: small.sav: Unrecognized record type 7, subtype 13 encountered in system file. >

Dear Users, I am new to both of things, so do not blame me too much... I am busy with semiparametric regression and use WinBUGS to sample posteriors. The code to call Winbugs is as follows: data <- list("y","X","n","m") #My variables inits.beta <- rep(0,K) inits.beta0 <- 0 inits <-

Hi, I have a dataset with the binary outcome Y(0,1) and 4 covariates (X1,X@,X#,X$). I am trying to use MCMClogit to model logistic regression using MCMC. I am getting an error where it doesnt identify the covariates ,although its reading in correctly. The dataset is a sample of actual dataset. Below is my code: > ####################### > > > #retreive data > # considering four

Hi all, there appears to be something strange with the plotting of tables of 1 dimension; if I attempt to make a plot of a table of characters with only 1 value I get an error (Error in xy.coords(x, y, xlabel, ylabel, log) : 'x' and 'y' lengths differ). With more than one value I don't get errors, neither with integers (even if only 1 value): tbl.char1 <-

Hi all, there appears to be something strange with the plotting of tables of 1 dimension; if I attempt to make a plot of a table of characters with only 1 value I get an error (Error in xy.coords(x, y, xlabel, ylabel, log) : 'x' and 'y' lengths differ). With more than one value I don't get errors, neither with integers (even if only 1 value): tbl.char1 <-