similar to: library(qpcR) cbind.na

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 all, Is there anyway too generate MA plot for 2 qPCR assays (an array of 2x 400). -- View this message in context: http://r.789695.n4.nabble.com/Bioconductor-MA-plot-for-qPCR-array-tp4182805p4182805.html Sent from the R help mailing list archive at Nabble.com.

I am using R on a Windows XP professional platform. The following code is part of a bigger one CODE press=function(y,x){ library(qpcR) models.press=numeric(0) cat("\n") dep=y print(dep) indep=log(x) print(indep) yfit=dep-PRESS(lm(dep~indep))[[2]] cat("\n yfit\n") print(yfit) yfit.orig=yfit presid=y-yfit.orig press=sum(presid^2)

Hi! Is There a way to manually create an affybatch object from qPCR array data? -- View this message in context: http://r.789695.n4.nabble.com/Creating-affybatch-objects-from-matrix-data-from-qPCR-array-tp3921559p3921559.html Sent from the R help mailing list archive at Nabble.com.

Inline. -- Bert On Tue, Apr 26, 2016 at 2:25 PM, Andr? Luis Neves <andrluis at ualberta.ca> wrote: > Ok. I`m trying to run a Poisson glmm with an observation-level random > intercept. But I`m getting the following error for the 'Baci' variable: > > 'Error: (maxstephalfit) PIRLS step-halvings failed to reduce deviance in > pwrssUpdate'. I guess this message

Ok. I`m trying to run a Poisson glmm with an observation-level random intercept. But I`m getting the following error for the 'Baci' variable: 'Error: (maxstephalfit) PIRLS step-halvings failed to reduce deviance in pwrssUpdate'. I guess this message is because the baci variable is not a an integer, and cannot be transformed into an integer as R has a threshold of 2x10^9 even in

I am using LOF.test() function from the qpcR package and got the following result: > LOF.test(nlregmod3) $pF [1] 0.97686 $pLR [1] 0.77025 Can I conclude from the LOF.test() results that my nonlinear regression model is significant/statistically significant? Where my nonlinear model was fitted as follows: nlregmod3 <- nlsr(formula=y ~ theta1 - theta2*exp(-theta3*x), data =

Hi, Many apologies for sending this twice. I accidentally hit the send button before I finished writing my mail. I am new to R and I hope someone can help me with my problem. I am trying to draw a side by side barplot. There is a main experiment and there are many sub experiments within the main experiment. I would like to draw a bar plot showing the number and type of sub_experiments done for

Hej, Calling newuoa (from the minqa package) makes R crash when the package rgl is loaded first. This however only on certain selected data. The data used for testing (saved to 'bugs.R'): xvals = c(1,2,4,5,7,8,9,10,11,12,14,15,16,18,19,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36) yvals =

Hi, I am looking to build even quintiles for a set of data. I managed to get it done, but I would like to know if there is a more direct way to write the data from my loop output x in the bottom of the code into the "empty" matrix p1, which I filled with NA''s. The way I am doing it at the moment is, more or less adding the matrix x after p1 and then deleting in a second step

> On Apr 10, 2016, at 9:38 AM, David Winsemius <dwinsemius at comcast.net> wrote: > >> >> On Apr 10, 2016, at 3:11 AM, Murray Efford <murray.efford at otago.ac.nz> wrote: >> >> Martin - >> Thanks, but although hatvalues() is useful for calculating PRESS, I can't find anything directly relevant to my question in the influence help pages. After

Hi, I'm having a problem getting the panel.average function to work as I expect it to in a lattice plot. I wish to draw lines between the averages of groups of y-values at specific x-values. I have created a dataset below which is similar to my real data. I also show an example of using panel.loess in place of panel.average; it performs in a manner similar to what I want panel.average to do

Hi I get the following error when I try and get the AICc for a gls regression using qpcR: > AICc(gls1) Loading required package: nlme Error in n/(n - p - 1) : 'n' is missing My gls is like this: > gls1 Generalized least squares fit by REML Model: thercarnmax ~ therherbmax Data: NULL Log-restricted-likelihood: 2.328125 Coefficients: (Intercept) therherbmax 1.6441405

I am currently trying to write a program that minimises the amount of work required for “auditable” qPCR data. At the moment I am using an Excel (.csv) spreadsheet as source data that has been transposed to the column format required for R to read. Unfortunately, this means I have* *to manually confirm the whole data set prior to doing any analysis, which is taking a considerable amount of time!

Can you explain why you need them as 'integer', A floating point representation can hold a value upto ~4.5e15 as an "integer" keeping the precision that you might need. Jim Holtman Data Munger Guru What is the problem that you are trying to solve? Tell me what you want to do, not how you want to do it. On Tue, Apr 26, 2016 at 1:11 PM, Andr? Luis Neves <andrluis at

> On Apr 10, 2016, at 3:11 AM, Murray Efford <murray.efford at otago.ac.nz> wrote: > > Martin - > Thanks, but although hatvalues() is useful for calculating PRESS, I can't find anything directly relevant to my question in the influence help pages. After some burrowing in the literature I'm doubting there is an answer out there (PRESS R^2 is always presented in a fairly

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)}