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I want to implement the following algorithm in R: I want to split my data, use a t test to compare both means of the groups to see if they significantly differ from each other. If this is a yes (p < alpha) I want to split again (into 4 groups) and do the same procedure twice, and stop otherwise (here the problem arises). As a final result I would have different groups of data. I made some

Hello, we have 80 text files with matrices. Each matrix represents a map (rows for latitude and columns for longitude), the 80 maps represent steps in time. In addition, we have a vector x of length 80. We would like to compute a regression between matrices (response through time) and x and create maps representing coefficients, r2 etc. Problem: the 80 matrices are of the size 4000 x 3500 and we

I have a scatter plot with 10000 points.? I would like to add a line that bins every 50 points and connects the average of each bin.? I'm looking for something similar to line type "m" in Stata. With this dataset of 10000 points, I would also like to bin the data and make boxplots at certain intervals, so that I have a set of boxplots to represent each bin.? I would also like the

Hi R users, I'm kind stuck in my R experience... I want to have a multiple barchart with n windows, but with the same background for each window, and I want that background to be a recorded dotplot. First, is it possible ? If so, I guess I have to call a record plot in the panel function but how ? As there is no panel.plot and I can't use the recorded plot as an argument for the

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The following C code : #include <stdio.h> #include <stdlib.h> int TESTE2( int parami , int paraml ,double paramd ) { int varx=0,vary; int nI =0; //varx= parami; if( parami > 0 ) { varx = parami; vary = varx + 1; } else { varx = vary + 1; vary = paraml; } varx = varx + parami + paraml; for( nI = 1 ; nI <= paraml; nI++) { varx =

Hello, I want to plot several lines to a main plot but at the end of each loop, it erases the last one. Here my program: alpha<-5 beta<-10 var<-0.5 s<-runif(1000,0,50) m<-length(s) variancealpha<-0.002 variancebeta<-0.051 variancevar<-0.001 alphachap<-vector() betachap<-vector() varchap<-vector() epsilon<-vector() b<-vector()

Hello, I created an array to hold the results of a series of simulations I'm running: d.eta <- array(0,dim=c(3,3,200)) <simulation goes here and populates the array but it's not important> Then I tried to save the results using this: save(d.eta,file="D:/Simulation Results/sim 9-23-11 deta") When I later tried to reload them using this: d.eta <-

Hi, as an R-beginner, I have a recoding problem and hope you can help me: I am working on a SPSS dataset, which I loaded into R (load("C:/...) I have 2 existing Variables: "ID" and "X" , and one variable to be computed: meanX.dependID (=mean of X for all rows in which ID has the same value) ID = subject ID. Since it is a longitudinal dataset, there are repeated

The following C test program was compiled using LLVM with -O3 option and MSVC with /O2. The MSVC one is about 600 times faster than the one compiled with the LLVM. We can see that the for loop in MSVC assembler is solved in the optimization pass more efficiently than that in LLVM. Is there an way to get a optimization result in LLVM like that of the MSVC? Manoel Teixeira #include

Hi, I am working on an example about generalized linear model in a paper using glm( ). The code is quite simple and straightforward, but the result is rediculous. The true parameter is c(4, -6), but the result is c(2.264774, -3.457114) Can anybody tell me the reason for this? Thanks a lot!!! Here is the code: g=function(t){exp(t)/(1+exp(t))} #the given link function n = 100 # sample size

Dear all, Being a newbie to R, I've trawled through many old posts on this list looking for a solution to my problem, but unfortunately couldn't quite figure it out myself. I'd be very grateful if someone here on this list could perhaps help me out. I have a lattice plot with several panels and would like to add some text next to the y-axis on the right hand side of each row of

The R translation teams have done a great job in making R usable for people who do not have English as their mother tongue. However, even within English speaking countries, there are groups which have trouble with the language, and it may be valuable to support the Sociolects of these groups too. Thanks to a generous contribution from Lars Polifo, these features will be made available in an

Hola a todos, Partiendo de: library(ggplot2); library(data.table) datos <- data.table(Date = seq.Date(as.Date("2017-01-01"), as.Date("2017-01-10"), by = "day"), V1 = rnorm(10), V2 = rnorm(10)) Quiero crear una función para pintar un gráfico cuyos argumentos sean

R users, I have df like this a <- data.frame( indx = 1:20, var1 = rep(c("I20", "I40", "A50", "B60"), each=5), var1_lab= rep(c("cat", "dog", "mouse", "horse"), each=5), var2 = rep(c("B20", "X40", "D50",

Is there an efficient way to use rbind() with the five dataframes described in the following example: a <- c(1:5) list.foo <- lapply(a, function(x) data.frame(beta=a*rnorm(10), deta=a*rnorm(10))) big.data.frame <- rbind(list.foo[[1]], list.foo[[2]], list.foo[[3]], list.foo[[4]], list.foo[[5]]) #is there an easier method? For example, I naively thought you could do something like

I am getting a difference in results when running some analysis using by and tapply compare to using a for loop. I've tried searching the web but had no luck with the keywords I used. I've attached a simple example below to illustrates my problem. I get a difference in the mean of yvar, diff and the p-value using tapply & by compared to a for loop. I cannot see what I am doing wrong.

Hi everyone, I'm working on a script trying to use foreach %dopar% but without success, so I manage to run the code with foreach %do% and looks like this: The code is part of a MCMC model for projects valuation, returning the most important results (VPN, TIR, EVA, etc.) of the simulation. foreach (simx = NsimT, .combine=cbind, .inorder=FALSE, .verbose=TRUE) %do% { MCPVMPA = MCVAMPA[simx]

Buen día para todos los que ven este correo. En estos días estoy estudiando la potencia de una prueba en inferencia, pero no entiendo bien como correr un codigo que lo haga pertinentemente, el codigo que corro es el siguiente, la idea es que a medida que crece el tamaña muestral pues la potencia de la prueba aumente, pero no se como hacer para que, repita la prueba variando el tamaño de la

Hi, If I try to do this: if(is.R()) data("eg1.DSE.data.diff", package="dse1") model <- est.VARX.ls(eg1.DSE.data.diff) (Page 14 - DSE Package Manual) I obtain a Segment Violation. I use R-1.3.0 and the last dse package version Maximino Ameneiro Gomez -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read