similar to: Matrix manipulation in for loop

Hi there, I have a the following function which takes a name(fname), total number of rows (Total), number of times to make a sample(nSample), number of records/rows to be included in each sample(nPatient). then it generates required samples and calculates the mean and standard deviation of the columns for each sample and finally in calculates the grand mean and standard deviation. The problem

Dear R developers and users: I have the following data, x is the response vaiable, nsample(individual) nested within trt, and subsample nested within nsample, I want to fit trt as fixed effect, and block, nsample(trt) as random effects using lme, is the following coding correct? dat$vgrp <- getGroups(dat, form = ~ 1|trt/nsample, level = 2) ge.lme1 <- lme(fixed=x~trt, data=dat,

Hi, I am new to clustering and was wondering why pvclust using "maximum" as distance measure nearly always results in p-values above 95%. I wrote an example programme which demonstrates this effect. I uploaded a PDF showing the results Here is the code which produces the PDF file: ------------------------------------------------------------------------------------- s <-

Hi, I'm new to R (and statistics) and my boss has thrown me in the deep-end with the following task: We want to evaluate the impact that sampling size has on our ability to create a robust model, or evaluate how robust the model is to sample size for the purpose of cross-validation i.e. in our current project we have collected a series of independent data at 250 locations, from which

I wonder if someone could help me adjusting the following code to parallelized snow code: #Creating a data set (not needed to be parallel) n<-100 p<-100 x<-matrix(rnorm(n*p),p) y<-rnorm(n) # Bootstrapping nboot<-1000 alpha<-0.05 rhoboot <- array(0, dim=c(p,nboot)) bootranks <- array(0, dim=c(p,nboot)) bootsamples <- array( floor(runif(n*nboot)*n+1), dim=c(n,nboot)) for

Hello, If you want to bootstrap a statistic, I suggest you use base package boot. You would need the data in a data.frame, see how you could do it. library(boot) bootMedianSE <- function(data, indices){ d <- data[indices, ] fit <- rq(crp ~ bmi + glucose, tau = 0.5, data = d) ypred <- predict(fit) y <- d$crp median(y - ypred)^2 } dat <-

Dear R-experts, I am trying to bootstrap (and average) the median squared error evaluation metric for a robust regression. I can't get it. What is going wrong ? Here is the reproducible example. ############################# install.packages( "quantreg" ) library(quantreg) crp <-c(12,14,13,24,25,34,45,56,25,34,47,44,35,24,53,44,55,46,36,67) bmi

Hello, &nbsp; I want to sum first three terms of each column of matrix. But I don't calculate with "apply" function. &nbsp; skwkrt&lt;-function(N=10000,mu=0,sigma=1,n=100, nboot=1000,alpha=0.05){ x&lt;-rnorm(N,mu,sigma)#population samplex&lt;-matrix(sample(x,n*nboot,replace=T),nrow=nboot) #... } &nbsp; is that: suppose a is a 5x2 matrix. &nbsp;a={1,2,3,4,5

Hello all, I am re-posting my previous question with a simpler, more transparent, commented code. I have been ramming my head against this problem, and I wondered if anyone could lend a hand. I want to make parallel a bootstrap of a linear mixed model on my 8-core mac. Below is the process that I want to make parallel (namely, the boot.out<-boot(dat.res,boot.fun, R = nboot) command).

Hello, My question likely got buried so I am reposting it in the hopes that someone has an answer. I have thought more about the question and modified my question. I hope tha my specific question is: I am attempting to create a bootstrap procedure for a finite sample using the theory of Rao and Wu, JASA (1988) that replicates within each strata (h) n_h - 1 times. To this end, I require a

Hi, I am using errorest function from ipred package. I am hoping to perform "bootstrap 0.632+" and "bootstrap leave one out". According to the manual page for errorest, i use the following command: ce632[i]<-errorest(ytrain ~., data=mydata, model=lda, estimator=c("boot","632plus"), predict=mypredict.lda)$error It didn't work. I then tried the

Hi everyone, I have a question about functions. I have two functions: Sampling=function(fname,Total,nSample,nPatient){......return(list(Gmean,Gsd))} Power=function(alfa,m1,m2,s1,s2,n1,n2){....return(powe)} I want to use "Gmean" and "Gsd" which are the returned values from "Sampling" function, in "Power" function. i.e. when I call "power" I want

Hallo everybody! I am trying to perform a TiTAN (Baker & King 2010) analysis with R 2.14.1. I have come that far: h89Abund <- read.csv("Fish89Abund.csv") > names (Fish89Abund) [1] "StationCode" "Abramisbrama" "Alburnoidesbipunctatus" "Alburnusalburnus" [5] "Ameiurusmelas" >

Hola, Quiero especificar una ecuación con varias variables explicativas de una manera eficiente sin necesidad de escribir todas y cada una. Tengo un conjunto de variables (junto con otras) dentro de una base de datos que se llaman pot23 pot311 pot312 pot 316 pot317........... pot80. No necesariamente están secuenciadas. Quisiera saber cómo indicar que incluya todas las variables de pot23 a pot80

Hi, I'm trying to plot the forecasts I generated using the Plot.Fore function of the BootPR package. But I got an error from zoo: My data: Time Series: Start = 1 End = 18 Frequency = 1 [1] 38731 38628 39117 92809 71984 31226 58613 72360 107956 92066 [11] 95208 99098 95848 120383 110717 105680 98469 101916 Script: y1<-ts(y1);

Hi, i am trying to run an ANCOVA and a bootstrapped ANCOVA analysis on a specific data set. I am using the ancova and ancboot functions as in the following code: setwd("C:/Users/User/Desktop/Rdatabilingualstudy2012") bilingualismdata<-read.spss("bilingualdataforconferences2012.sav", use.value.labels = TRUE, to.data.frame = TRUE)

Hi In the following codes, I had to choose between printing (= TRUE) or deliver something for grab (ei, vi). Is there a way to get both--that is, to print and also have ei and vi for grab? Thanks. Steven ... out<-round(as.data.frame(cbind(ap,se,t,p)),digits) out<-cbind(out,sig) out<-out[!grepl(colnames(zx)[1],rownames(out)),] if(printing){ cat("\nAPPs of bivariate ordered

Hi everybody! I would like to export the results of a test statistic in a *.csv file, but get an error. The code is below. The data are attached as .txt with tab as separator. I tried to get a sample dataset, but for some reason it didn't work, so please excuse the length of the file. I also attached a txt with the output (copy/paste) in case that helps. ---- > library(WRS) >

Hi, I wonder if anyone can help me with this issue. I am using R2BayesX. It seems that the model can maximally contain 20 interactions. When the number of interaction terms exceed 20, the code stops working. Here is a piece of toy code. rm(list=ls()) library(BayesX) library(R2BayesX) #data generating model f2<-function(x1,x2,x3,x4) { y<-2*sin(pi*x1)*1.5+exp(2*x2)/3+2 * sin(4 * pi * (x3

?s 09:51 de 11/08/2024, Steven Yen escreveu: > Hi > > In the following codes, I had to choose between printing (= TRUE) or > deliver something for grab (ei, vi). Is there a way to get both--that > is, to print and also have ei and vi for grab? Thanks. > > Steven > > ... > > out<-round(as.data.frame(cbind(ap,se,t,p)),digits) > out<-cbind(out,sig) >