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I want to use function cbind.na at library(qpcR) I install package qpcR and I can use functions such m1 <- pcrfit(reps, 1, 2, l5) > AICc(m1) [1] -102.5843 but when i try cbind.na(1, 1:7) i take message Error: could not find function "cbind.na" Thanks -- View this message in context: http://r.789695.n4.nabble.com/library-qpcR-cbind-na-tp4023339p4023339.html Sent from the

Suppose i have matrix z id<-c(1,2,3,4,5) a <- c(4, 3, 2, NA, 1) b <- c(3, NA, 2, 7, 1) c <-c(3, NA, NA, 7, NA) z<- cbind(id,a, b,c) id a b c [1,] 1 4 3 3 [2,] 2 3 NA NA [3,] 3 2 2 NA [4,] 4 NA 7 7 [5,] 5 1 1 NA I want to select those columns for which I have the smallest number of NA In my example, these would be column1 and 2 since they give me 4 3 2 2

Dear users, *******I have a function f to simulate data from a model (example below used only to show my problems) f<-function(n,mean1){ a<-matrix(rnorm(n, mean1 , sd = 1),ncol=5) b<-matrix(runif(n),ncol=5) data<-rbind(a,b) out<-data out} *********I want to simulate 1000 datasets (here only 5) so I use S<-list() for (i in 1:5){ S[[i]]<-f(n=10,mean1=0)} ******I have a

I have matrix data data<-matrix(cbind(c(0,0,0),c(NA,0,1),c(1,1,1),c(0,1,1)),ncol=3) and I want to create a new matrix by checking each element of the data and put value 0 if i have NA and 1 otherwise. For this reason i made the function below pdata<-matrix(NA,ncol=ncol(data),nrow=nrow(data)) pdata<-sapply(1:nrow(data),function(i) sapply (1:ncol(data),function(j) if (is.na(data[i,j]))

I generate and save a dataset For example exampledata<-runif(10) library("R.utils"); saveObject(exampledata, file="exampledata_9810.RData"); exampledata_9810<- loadObject("exampledata_9810.RData"); I use ex function to make alot of calculations using sink to export results (in this simply example only summary of dataset) ex<-function(data){

Dear users, *******I have a function f to simulate data from a model (example below used only to show my problem) f<-function(n,mean1){ a<-matrix(rnorm(n, mean1 , sd = 1),ncol=5) b<-matrix(runif(n),ncol=5) data<-rbind(a,b) out<-data out} *********I want to simulate 1000 datasets (here only 5) so I use S<-list() for (i in 1:5){ S[[i]]<-f(n=10,mean1=0)} ******I have a very

For my problem I have #Constraints b11<-0 b21<-0 b12<-0 b22<-0 n1>=0 n2>=0 n1<=1 n1<=1 n1+n2=1 In order to use spg I set Amat<-matrix(rbind(c(rep(0,10)),c(rep(0,10)),c(rep(0,2),1,rep(0,7)), c(rep(0,3),1,rep(0,6)),c(rep(0,10)),c(rep(0,10)), c(rep(0,6),1,rep(0,3)),c(rep(0,7),1,rep(0,2)), c(rep(0,8),1,rep(0,1)),c(rep(0,9),1,rep(0,0)),

Hello, users. Dear users, *******I have a function f to simulate data from a model (example below used only to show my problems) f<-function(n,mean1){ a<-matrix(rnorm(n, mean1 , sd = 1),ncol=5) b<-matrix(runif(n),ncol=5) data<-rbind(a,b) out<-data out} *********I want to simulate 1000 datasets (here only 5) so I use S<-list() for (i in 1:5){ S[[i]]<-f(n=10,mean1=0)}