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Hi all. Belove is the example from the cluster-help page wtih the output. I simply cannot figure out how to relate the estimate and robust Std. Err to the p-value. I am aware this a marginal model applying the sandwich estimator using (here I guess) an emperical (unstructered/exchangeable?) ICC. Shouldent it be, at least to some extend, comparable to the robust z-test, for rx :

Hello, I have a statistical problem that I am using R for, but I am not making sense of the results. I am trying to use multiple regression to explore which variables (weather conditions) have the greater effect on a local atmospheric variable. The data is taken from a database that has 20391 data points (Z1). A simplified version of the data I'm looking at is given below, but I have a

Shouldn't the F statistic (and p value) for the x2 term in the following calls to anova() and add1() be the same? I think anova() gets it right and add1() does not. > d <- data.frame(y=1:10, x1=log(1:10), x2=replace(1/(1:10), 2:3, NA)) > anova(lm(y ~ x1 + x2, data=d)) Analysis of Variance Table Response: y Df Sum Sq Mean Sq F value Pr(>F) x1 1

Dear all, I am attempting to explain patterns of arthropod family richness (count data) using a regression model. It seems to be able to do a pretty good job as an explanatory model (i.e. demonstrating relationships between dependent and independent variables), but it has systematic problems as a predictive model: It is biased high at low observed values of family richness and biased low at

Dear R Should I be concerned if the loadings to a Principle Component Analysis are as follows: Loadings: Comp.1 Comp.2 Comp.3 Comp.4 X100m -0.500 0.558 0.661 X200m -0.508 0.379 0.362 -0.683 X400m -0.505 -0.274 -0.794 -0.197 X800m -0.486 -0.686 0.486 0.239 Comp.1 Comp.2 Comp.3 Comp.4 SS loadings 1.00 1.00 1.00 1.00 Proportion Var 0.25 0.25 0.25

Hello I've created a 3d scatterplot, and had no problems labeling the points. However, I've been really struggling to change the color of the points based on a factor (see 'group' below). Is such a thing possible? My data look like this: food group x y z apple fruit 0.216 -0.112 -0.893 orange fruit 0.814 0.097 0.460 broccoli veg -0.239 0.240 -0.425 banana

Dear R users I have a big matrix like 6021 1188 790 290 1174 1015 1990 6613 6288 100714 6021 1 0.658 0.688 0.474 0.262 0.163 0.137 0.32 0.252 0.206 1188 0.658 1 0.917 0.245 0.331 0.122 0.148 0.194 0.168 0.171 790 0.688 0.917 1 0.243 0.31 0.122 0.15 0.19 0.171 0.174 290 0.474

rm(list=ls()) yx.df<-read.csv("c:/MK-2-72.csv",sep=',',header=T,dec='.') dim(yx.df) #get X matrix y<-yx.df[,1] x<-yx.df[,2:643] #conver to matrix mat<-as.matrix(x) #get row number rownum<-nrow(mat) #remove the constant parameters mat1<-mat[,apply(mat,2,function(.col)!(all(.col[1]==.col[2:rownum])))] dim(yx.df) dim(mat1) #remove columns with numbers of

Hi! Some background: I am trying to create an application that would encode video taken by USB camera using Theora and then send it to the client. I have almost succeeded, but I have one problem. When I grab video frames from the camera and encode them they form 4KB OGG pages, then I send them over TCP/IP to the client application. Since I want to achieve as small latency as possible I

Hi R community! I've fitted three mixed-effects regression models to a thousand bootstrap samples (case-resampling regression) using the lme4 package in a custom-built for-loop. The only output I saved were the inferential statistics for my fixed and random effects. I did not save any output related to the performance to the machine learning algorithm used to fit the models (REML=FALSE).

Hi, I am getting a warning message when I am fitting a generalized linear mixed model (m1.2 below). CHOLMOD warning: matrix not positive definite Error in objective(.par, ...) : Cholmod error `matrix not positive definite' at file:../Supernodal/t_cholmod_super_numeric.c, line 614 Any idea? Thanks for your help, Reza > sessionInfo() R version 2.4.1 (2006-12-18) i386-pc-mingw32

Dear all,I am a new user of WinBUGS and need your help. After running the following code, I got parameters of beta0 through beta4 (stats, density), but I don't know how to get the prediction of the last value of h, the variable I set to NA and want to model it using the following code.Does anyone can given me a hint? Any advice would be greatly appreciated.Best

Hi, I am performing a two-way ANOVA (2 factors with 4 and 5 levels, respectively). If I'm interpreting the output of summary correctly, then the interaction between both factors is significant: ,---- | ## Two-way ANOVA with possible interaction: | > model1 <- aov(log(y) ~ xForce*xVel, data=mydataset) | | > summary(model1) | Df Sum Sq Mean Sq F value Pr(>F) |

Dear All, I have two factors: GROUP and PATIENT, where PATIENT is nested within GROUP. >levels(example$GROUP) [1] "0" "1" "2" "3" "4" > levels(example$PATIENT) [1] "1" "2" "3" There are three observations at each combination of these factors. However, there are no observations for PATIENT = 3 and GROUP

hello, i'm pete ,how can i order rows of matrix by max to min value? I have a matrix of membership degrees, with 82 (i) rows and K coloumns, K are clusters. I need first and second largest elements of the i-th row. for example 1 0.66 0.04 0.01 0.30 2 0.02 0.89 0.09 0.00 3 0.06 0.92 0.01 0.01 4 0.07 0.71 0.21 0.01 5 0.10 0.85 0.04 0.01 6 0.91 0.04 0.02 0.02 7 0.00 0.01 0.98 0.00 8 0.02

I'm an R novice and my colleagues are about to convince me to get my data into SPSS, which will presumably be easier for someone who doesn't live in R to point and click his way into some kind of analysis that might be meaningful. I've got two groups of subjects (classkey in the table below). They've each received several different treatments. One measure is a 1-7 rating taken

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

After ordering the table of membership degrees , i must get the difference between the first and second coloumns , between the first and second largest membership degree of object i. This for K=2,K=3,....to K.max=6. This difference is multiplyed by the Crisp silhouette index vector (si). Too it dependending on K=2,...,K.max=6; the result divided by the sum of these differences I need a final

Hi, dear all: I am a beginner. I appreciate any help or hint from you. I am trying to do calculation with matrices. I have 3 matrices. One is matrixA, 2nd is matrixB, and last is matrixC. Here is matrixA: 1.8511.40.0831.001 0.8771.30.1161.33 1.9021.21.1020.302 0.8640.1261.110.252 1.8230.2161.0020.307 Next is matrixB: 0.8761.770.1930.328 0.8911.0090.2381.004

Hello all, I would like to connect two IPv4-only networks through global IPv6-only network with tinc. Could anyone tell me how to configure tinc.conf and the other config files? Thanks in advance, Ichiro Tinc: Discussion list about the tinc VPN daemon Archive: http://mail.nl.linux.org/lists/ Tinc site: http://tinc.nl.linux.org/