similar to: problem about t test

Dear all, Hi, I have the problems about converting the matrix to adjacency matrix.Here's my example, a b c d e fa 1.0000000 0.4048823682 0.1228531 0.49046991 0.4945158868 0.307443317b 0.4048824 1.0000000000 0.4367475 0.96949219 0.0007378596 0.560747765c 0.1228531 0.4367474719 1.0000000 0.40037341 0.3157538204

Hello, I'd like to normalize a data frame which are "45000 obs. of 212 variables".I want to normalize the data frame by each row. But I failed.Here is my R code, can you tell me where am I wrong? > bb<-function(normalize) (dat[i,]-min(dat[i,]))/(max(dat[i,])-min(dat[i,]))> dat1<-apply(dat,1,bb) Thanks!! vie

Hi, I'm trying to build R packages. My package name is TEST. (/Users/apple/Documents/R/TEST)I type something in Terminal.But it showed an error... applede-macbook-pro:~ apple$ R CMD BUILD TESTError: cannot change to directory 'anRpackage1' I don't know where is wrong...Hope that you could help me!! Thank you!! Best Regards,Gina

Hi, I'm new to R language. There is a problem I couldn't understand. Hope you can answer my question. when i type >for (i in 1:10){ + print(sample(9,4,replace=T)) +} and it shows ten of four numbers and how do I do to calculate the frequencies in each list? I know there is a hint; list10<-vector(mode="list",length=4) But I don't know how to

Hello fellow R people, I can not figure out a pretty way to use strplit with vectors Imagine that I got the following data from someone with ID's representing several factors ID data A1-B1-t1 0 A1-B1-t2 1 A1-B2-t1 5 A1-B2-t2 10 A1-B10-t1 0 A1-B10-t2 1 A1-B20-t1 5 A1-B20-t2 10 ... I would like to turn this dataframe to station substation time data A1 B1 t1 0 A1 B1 t2 1 A1 B2 t1 5

I have been trying to pass a collection_select parameter and a text field parameter to observe_field so that it watches both the parameters simultaneously. but what i can see is , when i select some value from drop down and dont write anything in text field its giving correct results.parameters are also correct passed, but just after that if i write something in text field that value also get

Dear helpers, I wrote a code which estimates a multi-equation model with generalized least squares (GLS). I can use GLS because I know the covariance matrix of the residuals a priori. However, it is a bit slow and I wonder if anybody would be able to point out a way to make it faster (it is part of a bigger code and needs to run several times). Any suggestion would be greatly appreciated. Carlo

I am fitting models to the responses to a questionnaire that has seven yes/no questions (Item). For each combination of Subject and Item, the variable Response is coded as 0 or 1. I want to include random effects for both Subject and Item. While I understand that the datasets are fairly small, and there are a lot of invariant subjects, I do not understand something that is happening

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",

Dear R listers, I know I'm breaking the rules by asking a "homework" related question-- I hope you'll forgive me. I am a social psychology graduate student, and the only one in my department who uses R. I successfully completed my multiple regression and structural equation modeling courses using R (John Fox's car and sem packages were a big help, as was his book).

On 6 November 2012 22:28, Daniel Dunbar <daniel at zuster.org> wrote: > Is it possible instead to refactor the tests so that each binary corresponds > to one test? For example, look at how Hal went about integrating TSVC: It should be possible. I'll have to understand better what the preamble does to make sure I'm not stripping out important stuff, but also what to copy to

I'm hoping that this is a relatively easy question for someone familiar with the lme4 package. I'm accustomed to using HLM software and writing a simple 2 level [null] equation like this: L1 - Yij = b0 + e L2 - b0 = B00 + u0 The following command in R provides results that are identical to the HLM program. results <- lmer( Y ~ 1 |id , PanelData4) I can't

Hi all, I got a question on loop exit condition identification based on LLVM. I made an assumption first that loop exit conditions are located in exiting basic blocks. Then I use loop->getExitingBlocks() to get all BBs. However, this policy seemed not work for combinational exit conditions, e.g. compounding conditions consists of conditions with logical predicates. *The problem is that

R, I want to get means and confidence limits on the original scale for the treatment effect after running a mixed model. The data are: response<-c(16,4,5,8,41,45,10,15,11,3,1,64,41,23,18,16,10,22,2,3)

Hi, the german telco Colt Telekom has assigned the phone number block 56830-xxx to one of our customers. In the diaplan we have setup extensions like the following ones: exten => 56830910,1,Answer() exten => 56830910,2,Dial(SIP/bduerring,10,tr) exten => 56830910,3,VoiceMail,u20 exten => 56830910,4,hangup exten => 56830910,103,VoiceMail,b20 exten => 56830910,104,hangup exten

R users, My intention is to take factors out of DF, create list of tables and export these tables separately using write.table or sink function. write.table writes tables out as DF:s, should I use sink instead? Here is my example: a <- data.frame( indx = 1:20, var1 = rep(c("I20", "I40", "A50", "B60"), each=5),

> > If one compares the random effect estimates, in fact, one sees that > > they are in the correct proportion, with the expected signs. They are > > just approximately eight orders of magnitude too small. Is this a bug? > > BLUPs are essentially shrinkage estimates, where shrinkage is > determined with magnitude of variance. Lower variance more > shrinkage towards

Hello, I'm facing a problem, using "optim" packeg. I've written a program and run it using the latest R version 2.8.1,but there was an error message as following: R version 2.7.2 (2008-08-25) # same result when I use R version 2.8.1,Copyright (C) 2008 The R Foundation for Statistical ComputingISBN 3-900051-07-0R is free software and comes with ABSOLUTELY NO WARRANTY.You are

I am fitting models to the responses to a questionnaire that has seven yes/no questions (Item). For each combination of Subject and Item, the variable Response is coded as 0 or 1. I want to include random effects for both Subject and Item. While I understand that the datasets are fairly small, and there are a lot of invariant subjects, I do not understand something that is happening here, and in

Hi, Does anyone know what the distribution for the product of two correlated normal? Say I have X~N(a, \sigma1^2) and Y~N(b, \sigma2^2), and the \rou(X,Y) is not equal to 0, I want to know the pdf or cdf of XY. Thanks a lot in advance. yu [[alternative HTML version deleted]]