similar to: Test on mu with multivariate normal distribution

I have a large R program that I am constantly running over and over again. At the beginning of this program, I create a hige matrix and a huge dataframe but these are constant. What I mean by constant is that, if I run the program over later, I really should just use the old matrix and dataframe ( if they exist ) that were created in a previous run so that the program doesn't have to spend

Dear folks, I?m trying to build a function to create and make available some variables I frequently use for testing purposes. Suppose I have a function that takes some inputs and creates (internally) several named objects. Say, fun1 <- function(x, y, z) {obj1 <- x; obj2 <- y; obj3 <- z <missing stuff> } Here is the challenge: After I run it, I want the objects to be

Dear All, I came across an error message recently when constructing a reference class, an example is attached below, it looks like only if I call a specific method in advance, otherwise it cannot be found in defined method without using .self, this make it difficulty that sometimes in my initialize method, I need to call other method defined in the same reference class, the workaround for this is

Dear list, I have developed a forward-time population genetics simulation environment simuPOP, which is a set of C++ (template) classes/functions wrapped by SWIG as Python libraries. R is used extensively as plotting and statistical analysis engine through RPy package. I use Python to wrap simuPOP since most the following can be easily done using SWIG or Python C API. However, since Python is

Hey all, I''m doing something of a node-node connection, and I want to eventually walk each node, pulling data from each node, and displaying the path. The DB table would just be columns of IDs that link to each other My catch is that these aren''t generic nodes, they are Models that could potentially connect to each other, and I don''t know how to

Hi all, Suppose I want to set the values in a column to the log of the values of another column like so: object$LogDist <- log10(object$Distance) How do I loop through the objects if I have object1, object2, etc to perform this function? object1$LogDist <- log10(object1$Distance) object2$LogDist <- log10(object2$Distance) object3$LogDist <- log10(object3$Distance) I was trying to

Hello all, Here is my GSoC 2012 proposal: Python bindings for LLVM. Any feedback are welcome! *Title: Python bindings for LLVM* *Abstract: * llvm-py provides Python bindings for LLVM. The latest llvm-py supports bindings with Python 2.x version for LLVM 2.x. This project is to improve llvm-py to make it compatible with both Python 2.x and Python 3 for LLVM 3. *Motivation* LLVM is used as a

Dear list, I have to draw a simple plot. On y axe some numerical values that correspond to various categories on axe x. The table I am reading looks like: cat Obj1 Obj2 Obj3 max 23 27 34 ave 21 25 32 min 19 23 30 In order to avoid that the first column is reordered alphabetically I used: (found here http://tolstoy.newcastle.edu.au/R/help/06/09/33808.html) a <- as.character(table$cat)

Hi! I use simtest fonction of multcomp package to compile a Dunnett's test. I have 10 treatments and one control group, so i create a matrix with: m<-matrix(0,10,11) m[1,1]<--1 m[1,2]<-1 m[2,1]<--1 m[2,3]<-1 m[3,1]<--1 m[3,4]<-1 m[4,1]<--1 m[4,5]<-1 m[5,1]<--1 m[5,6]<-1 m[6,1]<--1 m[6,7]<-1 m[7,1]<--1 m[7,8]<-1 m[8,1]<--1 m[8,9]<-1

# R for Windows will not send your bug report automatically. # Please copy the bug report (after finishing it) to # your favorite email program and send it to # # r-bugs at r-project.org # ###################################################### This report is joint from Richard Heiberger <rmh at temple.edu> and Burt Holland <bholland at temple.edu>. Burt Holland is the coauthor

Hi, all: Two examples are shown below. I want to use the multiple comparison of Dunnett. It succeeded in upper case "example 1". However, the lower case "example 2" went wrong. In "example 2", the function pmvt return NaN, so I cannot show this simtest result. Is there any solution? (I changed the variable "maxpts" to a large number in front of the

Hi, I've got a problem building a contrast matrix for the Dunnet contrast in package multcopm. The following works fine: > summary(simtest(adiff ~ trial)) Simultaneous tests: Dunnett contrasts Data: adiff by trial Contrast matrix: trial1 trial2 trial3 trial4 trial5 trial2-trial1 -1 1 0 0 0 trial3-trial1 -1 0 1 0 0

I have the following script for generating a dataset. It works like a champ except for a couple of things. 1. I need the variables "itbs" and "map" to be negatively correlated with the binomial variable "lunch" (around -0.21 and -0.24, respectively). The binomial variable "lunch" needs to remain unchanged. 2. While my generated variables do come out

I'm new to R, but I'm trying to write a program for a dissertation that generates a dataset as follows... subject=1:1000 treat=rbinom(1*1000,1,.13) gender=rbinom(1*1000,1,.5) eth=runif(1*1000, min=1, max=4) cogat=rnorm(1*1000, 100, 16) map=rnorm(1*1000, 200, 9) simtest=data.frame (subject=subject, treat=treat, gender=gender, eth=round(eth,digits=0),

Dear R-users I analysed the same data set by two different ways; analysis of covariance by using lm and anova functions and multiple comparison by using simtest function in the multcomp library. The output from the analysis of covariance is; > y<-lm(D~Cond+Q1,data=x) > anova(y) Analysis of Variance Table Response: D Df Sum Sq Mean Sq F value Pr(>F) Cond 2

Below is a second cut at all.equal and also a generic function test.equal which is intended to return a T/F value. The default method uses all.equal, which is the reason I was looking for all.equal in the first place. Prompted by Thomas Lumley's observation that a T/F result makes more sense I thought it would be worthwhile to indicate what I'm really doing. I have been using test.equal

Below is a third cut at all.equal and the generic function test.equal which is intended to return a T/F value. There was a suggestion that "is.equal" rather than "test.equal" might be considered as a name. I have mixed feelings about this. I associate the "is" functions with inheritance rather than comparisons, but the "equal" part of the name makes it

Hi everyone, have a small problem trying to converting a dataset in matrix form to an array. Specifically: data include 3D measurement -x,y,z of 59 points in 36 objects. They are stored as a matrix (x) of 2124 rows and 3 columns. What I want to do is to extract each subject's dataset using an array (b). Accordingly, I tried the following command: b<-array(a,c(59,3,36)). The problem is

hi list, i have to ask you again, having tried and searched for several days... i want to do a TukeyHSD after an Anova, and want to get the adjusted p-values after the Tukey Correction. i found the p.adjust function, but it can only correct for "holm", "hochberg", bonferroni", but not "Tukey". Is it not possbile to get adjusted p-values after

I'm not sure what the process is for this, but can I get the following all.equal function put in the R base? Paul Gilbert ____ all.equal <- function(obj1, obj2,...) {UseMethod("all.equal")} all.equal.default <- function(obj1, obj2, tolerance=.Machine$double.eps) {if(mode(obj1) != mode(obj2) ) return("modes differ.") if (length(obj1) !=