similar to: Vectorizing for weighted distance

[Please keep r-help in the cc: list] I don't quite know how to interpret the difference between specifying effort as an offset vs. as weights; I would have to spend more time thinking about it/working through it than I have available at the moment. I don't know that specifying effort as weights is *wrong*, but I don't know that it's right or what it is doing: if I were

Can someone explain why I am getting the following error: in the r code below? Error in solve.default(diag(2) + ((1/currvar) * (XX1 %*% t(XX1)))) : system is computationally singular: reciprocal condition number = 0 In addition: There were 50 or more warnings (use warnings() to see the first 50) The R code is part of a bigger program. ##sample from full conditional

On some systems (alpha), tick marks don't appear on plots. The easiest way to see the problem is something like: > plot(0:1,axes=FALSE) > axis(1,1:2) The problem is in X11_Line(...) from .../src/unix/devX11.c, which is so short I've included the whole function below: static void X11_Line(double x1, double y1, double x2, double y2, int coords, DevDesc *dd) {

Hi there: I have this configuration: |-----[Server 2] | [Internet]--------[Router]----------[Switch]------------ [Server 1] | |-----[PC1] | |-----[PC2] | |-----[PC3] Server 1 has IP 216.251.XXX.XX1 Server 2 has IP 216.251.XXX.XX2 PC1 has IP 216.251.XXX.XX3 PC2 has IP 192.168.XXX.1 PC3 has IP 192.168.XXX.2 How do I configure shorewall in SERVER 2 to block to/from the Internet Port 22

Dear all, I am stumped at what should be a painfully easy task: predicting from an lm object. A toy example would be this: XX <- matrix(runif(8),ncol=2) yy <- runif(4) model <- lm(yy~XX) XX.pred <- data.frame(matrix(runif(6),ncol=2)) colnames(XX.pred) <- c("XX1","XX2") predict(model,newdata=XX.pred) I would have expected the last line to give me the

I'm having problems with the iPhone client in the 1.1.1 version of the iPhone software. Things with other clients work fine, and the iPhone worked fine before it was upgraded to 1.1.1. Other phones on 1.1.1 failed. I'm still working on testing against the client with the iPhone 1.0.2 software on it. The problem is that the client simply doesn't connect to dovecot. I can see the

Hi, all When I am using mle.cv(wle), I find a interesting problem: I can't do leave-one-out cross-validation with mle.cv(wle). I will illustrate the problem as following: > xx=matrix(rnorm(20*3),ncol=3) > bb=c(1,2,0) > yy=xx%*%bb+rnorm(20,0,0.001)+0 > summary(mle.cv(yy~xx,split=nrow(xx)-1,monte.carlo=2*nrow(xx),verbose=T), num.max=1)[[1]] mle.cv: dimension of the split subsample

Hi all, I've taken preglows ARM versions of qmf_synth and iir_mem16 from rockboxes speex codec, and tweaked them a bit further for some more speed. I attach them here so you can review and take on any changes you want. Please let me know if you have questions etc. Thanks, Robin -- Robin Watts, Email: <mailto:Robin.Watts@wss.co.uk> Warm Silence Software, WWW:

Hi all, I have a very large binary vector, I wish to calculate the number of 1's over sliding windows. this is my very slow function slide<-function(seq,window){ n<-length(seq)-window tot<-c() tot[1]<-sum(seq[1:window]) for (i in 2:n) { tot[i]<- tot[i-1]-seq[i-1]+seq[i] } return(tot) } this works well for for reasonably sized vectors. Does

Greetings helpRs -- I would like to use plot() to plot two cumulative distribution curves so that a user of the plot can compare the distributions of the two variables. The following code draws two distributions separately, but I cannot find the instruction necessary to add a second cumulative distribution to the first one. Any suggestion would be very welcome. x1 <-

I''ve made some tests... eth2 is my internal interface, LAN is connected here. Before I had IMQ device in AB mode... PREROUTING [A]fter NAT, POSTROUTING [B]efore NAT. I want the same situation on ifb. I do this in this way: --- # incoming traffic here from LAN is before NAT tc qdisc add dev eth2 handle ffff: ingress # outcoming traffic here from WAN is after NAT tc qdisc add dev eth2

R-users E-mail: r-help@r-project.org Hi! R-users. http://finzi.psych.upenn.edu/R/library/mvpart/html/xpred.rpart.html says: data(car.test.frame) fit <- rpart(Mileage ~ Weight, car.test.frame) xmat <- xpred.rpart(fit) xerr <- (xmat - car.test.frame$Mileage)^2 apply(xerr, 2, sum) # cross-validated error estimate # approx same result as rel. error from printcp(fit) apply(xerr, 2,

Full_Name: Jörg Polzehl Version: 1.5.1 OS: Windows 2000 Submission from: (NULL) (193.175.148.198) When calculating MLE's in a variance component model using constrained optimization, i.e. optim(...,method="L-BFGS-B",...) I observed an inproper behaviour in cases where the likelihood function was evalueted at the constraint. Parameters and value of the function at the constraint

Hi! > How to do this ?? > To proceed with your answer on PICKUPMARK, where do I put this ??? Look at the example for Asterisk 1.4 on this page: http://www.voip-info.org/wiki/view/Asterisk+cmd+Pickup Philipp

Hello r-help! I have data with two kind of ratings on status of 100 occupations. The first kind of rating is on the percieved "objective" status that these occupations have in society at large, and the second kind or rating is on the status that the respondents think that these occuption *should* have. The ratings were originally integer values in the rage 1-9, but in the current data,

Hello, I have a specific problem, I have a large dataframe, and after clustering I want to select certain colums, the elements of a subcluster. My dataframe looks like this : > colnames(data) [1] "101KF4319097339" "102KF4319101170" "103KF4319047549" "104KF4319046389" [5] "105KF4319013260" "106KF4319025582"

Dear prospective reader, I apologize for posting my problem but I've just no idea how to go on by processing this huge (over 70 MB) dataset. Thank you in advance for any help or comment! I do appreciate it! My textfile contains 1 column of interest (numbers/values only). The overall issue is to extract 'events', starting points of which are defined by at least 24 preceding values

Hi All, I'm trying to do the following constrained optimization example. Maximize x1*(1-x1) + x2*(1-x2) + x3*(1-x3) s.t. x1 + x2 + x3 = 1 x1 >= 0 and x1 <= 1 x2 >= 0 and x2 <= 1 x3 >= 0 and x3 <= 1 which are the constraints. I'm expecting the answer x1=x2=x3 = 1/3. I tried the "constrOptim" function in R and I'm running into some issues. I first start off

Dear all, i would like to plot each value from my datasets as segment with defined transparency However, I didnt find out how to set the transparency. definition by "col=" in par() or segments() doesnt seem to work any suggestions? Thanks in advance. Kind regards, Robert Pazur example code: xx2 <-read.table("http://www.scandinavia.sk/data/R/0_05.csv", sep=";",

Hello all, I am rather new to lattice and have a simple question regarding formatting text labels on the axes. I have looked through my own archive on lattice notes, searched and examined 30 or so hits on Dr. Baron's search site, looked through my MASS book, my Data Analysis and Graphics Using R book, R news articles, and I have in my hand the lattice package instructions and have read and