similar to: expand the inside of command with rep ?

Hi, rstudio is very easy to install, but it would be great if it were just an apt-get away. Is there a reason it is not in Ubuntu main repos or in rrutter PPA? Kind regards, Xu

Dear All, I try not to bump too much, but I just tried Ubuntu 18.04, and it is not in repo and I still do not see any PPA available. If it would help, I can spend the time to explain why I believe it helpful to install using a command rather than webbrowser, but I think this is already understood why helpful, but it seems there is just a technical tricky problem to solve to implementation. Thank

Hi, The unique function is easy to understand and use. Beyond that, I want to get also the frequency of repetition of each individual row in a data frame Let me explain with an example : x<-data.frame(a=c(1,2,3,1,2),b=c(2,3,4,2,3),c=c(10,20,30,10,20)) xu<-unique(x) We have, > x ? a b? c 1 1 2 10 2 2 3 20 3 3 4 30 4 1 2 10 5 2 3 20 > xu ? a b? c 1 1 2 10 2 2 3 20 3 3 4 30 I want to get

Dear R-Help listers, I am trying to estimate an proportional odds logistic regression model (or ordered logistic regression) and then make predictions by supplying a hypothetical x vector. However, somehow this does not work. I guess I must have missed something here. I first used the polr function in the MASS package, and I create a data frame and supply it to the predict function (see below):

HI all, I'm new to R. Say I have a multi-layered list called newlist. ############ > str(newlist) List of 2 $ :List of 5 ..$ : num [1:8088] NA 464 482 535 557 ... ..$ : num [1:8088, 1:2] NA 464 482 535 557 ... ..$ : num [1:8088, 1:3] NA 464 482 535 557 ... ..$ : num [1:8088, 1:4] NA 464 482 535 557 ... ..$ : num [1:8088, 1:5] NA 464 482 535 557 ... $ :List of 3 ..$ : num

Hi list: This is my first time to post my question on the list. Thanks for your help. I am solving a quadratic programming using R. Here is my question: w = arg min 0.5*w'Mw - w'N s. t. sum(w) = 1; w>0 note: w is weight vector, each w_i must >=0, and the sum of w =1. Here is my R code: A <-matrix(c(2.26,1.26,1.12,1.12,2.27,1.13,1.12,1.13,2.2),3,3); B <-

Hi, I encountered a problem when I am trying to write my own function which contains another function. To simplify a problem, I tried the following simplified function, hope someone can idenfity the problem for me. I have a simple data frame called "testdata" as following: >

Does anyone know where I can find a changelog for MASS? It's difficult to know whether I should ask my company to update the package or not. We are usually required to show the changelog, but I can't find one. Thank you, Xu -- View this message in context: http://r.789695.n4.nabble.com/changelog-for-MASS-tp4034473p4034473.html Sent from the R help mailing list archive at Nabble.com.

  Hello R-users,   I have the following question, for which my search did not really return any usable result. If I have a matrix a1, and a vector a2 like below   a1<-matrix(c(1:4),2,2) a2<-c(8,9)   is there any function like the expand.grid (or some clever calling of the function) such that it outputs a matrix or dataframe where the entire a1 matrix is repeated for each value of a2 (the

Hi, Can you please help me with this please? What I am trying to do is call a vector from R function and used in the new function So I create 4 functions with these arguments M11 <- function(TrainData,TestData,mdat,nsam) { ls <- list() I have few statments one of them is vectx <- c(,1,2,3,4,5,6,6) vectz <- c(12,34,5,6,78,9,90) and then................ ls(vectx=vtecx,vectz=vectz)

Hello R community, I am attempting to run multiple logistic regressions (multinomial, via package 'nnet'), with Automated Model Selection (dredge, package 'MuMIn'). The aim is to reduce the number of predictor variables by assessing relative performance of each variable, which can be done in a coarse fashion using the Automated Model Selection option in package 'MuMIn'

Dear R listers, I am learning the MLE utility optim() in R to program ordered logit models just as an exercise. See below I have three independent variables, x1, x2, and x3. Y is coded as ordinal from 1 to 4. Y is not yet a factor variable here. The ordered logit model satisfies the parallel regression assumption. The following codes can run through, but results were totally different from what I

Dear All R Users, I am trying to graph a 3-D graph of simulated data for logit models using the powerful wireframe command, but I got stuck. Here are the codes: x <- seq(-4, 4, by=0.01) y <- seq(-4, 4, by=0.01) p <- 1/(1+exp(-0.12*x + 0.35*y)) mydata <- cbind(x, y, p) require(lattice) wireframe(p~x*y, data=mydata) and I received the following message: Error in

>cbn<-as.matrix(expand.grid( rep( list(0:1), 50))) Error in rep.int(rep.int(seq_len(nx), rep.int(rep.fac, nx)), orep) : invalid 'times' value In addition: Warning message: In rep.int(rep.int(seq_len(nx), rep.int(rep.fac, nx)), orep) : NAs introduced by coercion But I'm only interested in cbn matrix rows where: cbn<- cbn[rowSums(cbn)==5,] Is there a way to evaluate it

Hello, I've the following setting: (1) Data from a source without truncation (x) (2) Data from an other source with left-truncation at threshold u (xu) I have to fit a model on these these two sources, thereby I assume that both are "drawn" from the same distribution (eg lognormal). In a MLE I would sum the densities and maximize. The R-Function could be:

I want use survfit() and basehaz() inside a function, but it doesn't work. Could you take a look at this problem. Thanks for your help. Following is my codes: library(survival) n <- 50 # total sample size nclust <- 5 # number of clusters clusters <- rep(1:nclust,each=n/nclust) beta0 <- c(1,2) set.seed(13) #generate phmm data set Z <- cbind(Z1=sample(0:1,n,replace=TRUE),

Hello all, may be someone can give me a hint how to solve a little problem. I'm trying to create some expressions inside a for-loop which i want to evaluate AFTER this creation loop (but loop specific). To explain my problem here comes the code: y.mat <- t(matrix(rep(84:90,8) + as.numeric(gl(8,7)),nrow=7)) # > y.mat[1:2,] # [,1] [,2] [,3] [,4] [,5] [,6] [,7] # [1,] 85 86

Hello I have one DF (detheleny1periode), with some variables that mathes, in some way, variables in another DF (y2). The DF named detheleny1periode look like this (i have not included alle variables): CHR_NR diffdatoperiode 11377 29 11377 59 11377 78 with many different CHR_NR's. And the other DF named y2 look like this (i have not

I have a general question about coefficients estimation of the mixed model. I simulated a very basic model: Y|b=X*\beta+Z*b +\sigma^2* diag(ni); b follows N(0,\psi) #i.e. bivariate normal where b is the latent variable, Z and X are ni*2 design matrices, sigma is the error variance, Y are longitudinal data, i.e. there are ni

Hi R users, suppose I have two vectors, > x=c(1,2,3,4,5) > y=c('a','b','c','a','c') How can I get a data.frame like this? > xy count a 5 b 2 c 8 I know a few ways to fulfill the task. However, I have a huge number of this kind calculations, so I'd like an efficient solution. Thanks -- Best, Zhenjiang