similar to: Accessing matrix elements within a list

Dear list members. I have problems with the usage of cv.glm from the boot package. Here are some parts of the script I wanted to use: data <- read.table("selected_2D.csv", header=TRUE, sep=",") ? glm.fitted <- glm("ydata$ y ~ 1 + density + vsurf_ID6 + vsurf_S ", data=data) error <- cv.glm(data=data, glm.fitted, K=6) ydata$y is a separate data set, where

Hi, how are you? I am trying to replicate the binary data f(2) function in the attached document by starting with the simple example found below: observed <- matrix(c(0, 1, 0, 0, 1, 1, 1, 0, 0),3,3,byrow=TRUE) data <- matrix(c(1, 1, 0, 0, 1, 0, 0, 0, 1),3,3,byrow=TRUE) f2 = sum(probability of the matrix element where the matrix element is present in both the observed and the

Hi, I am a new user of R using R 2.8.1 in windows 2003. I have a csv file with single column which contain the 30,000 students names. There were typo errors while entering this student names. The actual list of names is < 1000. However we dont have that list for keyword search. I am interested in grouping/cluster these names as those which are similar letter to letter. Are there any

I am having a problem understanding the lda package. I have a dataset here: [,1] [,2] [,3] [1,] 2.95 6.63 0 [2,] 2.53 7.79 0 [3,] 3.57 5.65 0 [4,] 3.16 5.47 0 [5,] 2.58 4.46 1 [6,] 2.16 6.22 1 [7,] 3.27 3.52 1 If I do the following; "names(d)<-c("y","x1","x2") d$x1 = d$x1 * 100 d$x2 = d$x2 * 100 g<-lda( y ~ x1 + x2, data=d) v2

Hi Now a more theoretical question. I have two correlation matrices - one of a set of variables under a particular condition, the other of the same set of variables under a different condition. Is there a statistical test I can use to see if these correlation matrices are "different"? Thanks Mick

Hey, I am confused about how to generate the sample data from a mixture of Multivariate Gaussian ditribution. For example, there are 2 component Gaussian with prior probability of 0.4 and 0.6, the means and variances are u1=[1 1]', Cov1=[1 0;0 1] and u2=[-1 -1]', Cov2=[1 0;0 1] repectively. So how can I generate a sample of 500 data from the above mixture distribution? Thanks. Fred

Hi folks, I have a question about how to efficiently produce random numbers from Beta and Binomial distributions. For Beta distribution, suppose we have two shape vectors shape1 and shape2. I hope to generate a 10000 x 2 matrix X whose i th rwo is a sample from reta(2,shape1[i]mshape2[i]). Of course this can be done via loops: for(i in 1:10000) { X[i,]=rbeta(2,shape1[i],shape2[i]) } However,

Thanks David, Yes, I am talking about the MASS package.Thank you for pointing out that these scale the same. My question is, how do I get from the V1 data: V1 1 164.4283 2 166.2492 3 170.5232 4 156.5622 5 127.7540 6 136.7704 7 136.3436 to the other set of data: + 1 -2.3769280 + 2 -2.7049437 + 3 -3.4748309 + 4 -0.9599825 + 5 4.2293774 + 6 2.6052193 + 7 2.6820884 On Mon, Sep 28, 2009

Hi,   I'm a student in China, and I never used R before.   I'm now wondering how to simulate a sample of Markov chain of ,say 500 entries with a certain transition matrix.    Thanks a lot. ___________________________________________________________ 好玩贺卡等你发，邮箱贺卡全新上线！ http://card.mail.cn.yahoo.com/ [[alternative HTML version deleted]]

(sorry if this is a duplicate-problems with posting at my end) ---- Hello all, I need some help with a nice R-idiomatic and efficient solution to a small problem. Essentially, I am trying to eliminate randomly half of the entries in a vector that contains index values into some other vectors. More details: I am working with two strings/vectors of 0s and 1s. These will contain about 200

I have two matrix s1 and s2, each of them is 1000*1. and I have two equations: digamma(p)-digamma(p+q)=s1, digamma(q)-digamma(p+q)=s2, and I want to sovle these two equations to get the value of x and y, which are also two 1000*1 matrices. I write a program like this: f <- function(x) { p<- x[1]; q <- x[2]; ((digamma(p)-digamma(p+q)-s1[2,]) )^2 +((digamma(q)-digamma(p+q)-s2[2,]) )^2

Hello, are there any good methods in R that will test if two correlation matrices (obtained in different ways) are equal? Something better than the Mantel test would be preferable. Regards, Patrik Waldmann -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info",

Hi, I am very happy. My problems are solved without one little thing: (Iske <- matrix(c(1, 1, 1, 2, 2, 2, 1, 1, 1, 5, 1, 2, 2, 2, 1, 1, 1, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 5, 4, 4, 4, 4, 4, 4, 2, 2, 2, 2, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 1, 2), ncol = 5)) #My Matrix Iske<- Iske+33 #I want see the letters (Iske.char<-apply(Iske, 1, function(x) rawToChar(as.raw(x)))) #Numbers to

Dear all, I am having trouble creating summary tables using aggregate function. given the following table: Var1 Var2 Var3 dummy S1 T1 I 1 S1 T1 I 1 S1 T1 D 1 S1 T1 D 1 S1 T2 I 1 S1 T2 I 1 S1 T2 D 1 S1 T2 D 1 S2

Hi, I'm trying to get maximum likelihood estimates of \alpha, \beta_0 and \beta_1, this can be achieved by solving the following three equations: n / \alpha + \sum\limits_{i=1}^{n} ln(\psihat(i)) - \sum\limits_{i=1}^{n} ( ln(x_i + \psihat(i)) ) = 0 \alpha \sum\limits_{i=1}^{n} 1/(psihat(i)) - (\alpha+1) \sum\limits_{i=1}^{n} ( 1 / (x_i + \psihat(i)) ) = 0 \alpha \sum\limits_{i=1}^{n} (

I have some data 'myData' in wide form (attached at the end), and would like to convert it to long form. I wish to have five variables in the result: 1) Subj: factor 2) Group: between-subjects factor (2 levels: s / w) 3) Reference: within-subject factor (2 levels: Me / She) 4) F: within-subject factor (2 levels: F1 / F2) 5) J: within-subject factor (2 levels: J1 / J2) As this is the

On Tue, 12 Oct 2004 14:01:21 -0500 (CDT) Chris Lattner <sabre at nondot.org> wrote: > On Tue, 12 Oct 2004, Morten Ofstad wrote: > > > This is my first post on this mailing list, so bear with me... My name > > is Morten Ofstad and I work for Hue AS (www.hue.no), a company that > > makes 3D Visualization software. We are looking into using LLVM for JIT > >

Hi: How can I extract the dimension-names of a pre-defined element in a multidimensional array in R ? A toy example is provided below: I have a 4-dimensional array with each dimension having certain length. In the below example, "mydatastructure" explains the structure of my data. mydatastructure = array(0, dim=c(length(b),length(z),length(x),length(d)), dimnames=list(b,z,x,d)) where,

Hello there, I wish to solve the following nonlinear System of equations: + u1 - Vmax11*S1/(S1 + Km11 *(1 + S2/Km21)) - Vmax12*S1/( S1 + Km12 *(1+S2/Km22)) == 0 + u2 - Vmax22*S2/(S2 + Km22 *(1 + S1/Km12)) - Vmax21*S2/( S2 + Km21 *(1+S1/Km11)) == 0 + Vmax11*S1/(S1 + Km11 *(1 + S2/Km21)) + Vmax12*S1/( S1 + Km12 *(1+S2/Km22)) - d1*P1 == 0 + Vmax22*S2/(S2 + Km22 *(1 + S1/Km12)) + Vmax21*S2/( S2 +

I have three modules: ----------------------------------------------------------------- s1.ll: %0 = type <{ i32, i32 }> define void @s1(%0* byval %myStruct) nounwind { return: ret void } ----------------------------------------------------------------- s2.ll: %0 = type <{ i32, i32 }> define void @s2(%0* byval %myStruct) nounwind { return: ret void }