similar to: Car.proper C[] matrix

I'm new to bugs, so please bear with me. Can someone tell me if the following two models are doing the same thing? The reason I ask is that with the same data, the first (based on 4 separate coeffs a1--a4) takes about 50 secs, while the second (based on a vectorized form, a[]) takes about 300. The means are about the same, though R-hat's in the second version are quite a bit better.

Hi, I am trying to covert a Winbugs code into R code. Here is the winbugs code model{# model’s likelihoodfor (i in 1:n){time[i] ~ dnorm( mu[i], tau ) # stochastic componenent# link and linear predictormu[i] <- beta0 + beta1 * cases[i] + beta2 * distance[i]}# prior distributionstau ~ dgamma( 0.01, 0.01 )beta0 ~ dnorm( 0.0, 1.0E-4)beta1 ~ dnorm( 0.0, 1.0E-4)beta2 ~ dnorm( 0.0, 1.0E-4)#

I'm applying a function (Cov.f) defined below to each element of a distance matrix. When I run the code below, I get a warning message (below) and elements of returned matrix [2,3] and [3,2] are not zero as I would expect. Clearly, there is an error... What am I doing wrong? Thanks. --Dale Warning message: In if (h <= phi) { : the condition has length > 1 and only the first element

Hi, Is there anyone know if BUGS language allows the combination of variables as response such as Y[i] <- a*X1[i]+b*X2[i] Y[i] ~ dnorm(c,d) It seems doesn't work in my model. The problem is between two ######. The error message is > modelCheck("BayesBioMarker.BUGS") model is syntactically correct > modelData(paste("BUGS_data.txt",sep="")) data

hi all i would like to use r and winbugs in order to undertake seemingly unrelated regression. i am using the R2WINBUGS library. i just simulated a simple example (sample size is 25) in order to get the correct code. i suspect that the problem is in my definition of the prior. it wants a multivariate node. the example could be extended by including more than 1 X variable in the system of

Hi R users, I am trying to call openbugs from R. And I got the following error message: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ model is syntactically correct expected the collection operator c error pos 8 (error on line 1) variable ww is not defined in model or in data set [1] "C:\\DOCUME~1\\maomao\\LOCALS~1\\Temp\\RtmpqJk9R3/inits1.txt"

Hi. My friend has a problem that smbtar cannot recognize space character in specified filenames. He tried to execute following command line to back file "long file name" up: $ smbtar -s SERVER -p PASSWORD -x SHARE -u username -t /tmp/backup.tar \ "long file name" but smbtar tried to include three files as 'long', 'file' and 'name'. :-( Here is the

Dear Friends: I like so much to work with R program. Congratulations for your work. I need R for work with multivariate data. My question is: With the pairs(X) command my output is a pairwise scatterplot symmetric matrix. Like: | X1 |X1 vs X2|X1 vs X3|X1 vs X4| |X2 vs X1| X2 |X2 vs X3|X2 vs X4| |X3 vs X1|X3 vs X2| X3 |X3 vs X4| |X4 vs X1|X4 vs X2|X4 vs X3| X4 | It is

Dear list, I have a vector of characters and a list of two named elements : i <- c("a","a","b","b","b","c","c","d") j <- list(j1 = c("a","c"), j2 = c("b","d")) I'm looking for a fast way to obtain a vector with names, as follows : [1] "j1" "j1"

Hi, I'm analyzing a large number of large simulation datasets, and I've isolated one of the bottlenecks. Any help in speeding it up would be appreciated. `dat` is a dataframe of samples from a regular grid. The first two columns are the spatial coordinates of the samples, the remaining 20 columns are the abundances of species in each cell. I need to calculate the species richness in

Hello, I'm new to R and to Spatial Analysis and got a problem trying to create a Spatial Weights Matrix. *I us the following code to create the Neighbourslist:* >library(maptools) >library(spdep) >library(rgdal) >location_County<- readShapePoly("....") >proj4string(location_County)<- CRS("+proj=longlat ellps=WGS84") >location_nbq<-

Hi, is there any way to keep a sub matrix dimension? exemple : i1<-1; i2<-1 j1<-2; j2<-3; ret <-matrix(1,4,4)[i1:i2,j1:j2] ; dim(ret) is NULL because the submatrix single col or single row is coerce to a vector automaticaly. How can i bypass this cast : submatrix->vector ??????? Thank you. --------------------------------- [[alternative HTML version

Hello, These are implementations of strverscmp, scandir, alphasort and versionsort, and some test cases for them. I know these aren't in POSIX, but they're useful, nonetheless, and someone else might be interested in them. Regards, Luciano Rocha -- lfr 0/0 -------------- next part -------------- /* ----------------------------------------------------------------------- * * *

Hi, Having 3 dataframes with different row numbers, but equal column names (see below) I want to merge them by Var1 so I've tried: merge(j1,j2,j3,by="Var1") merge(j,j1,j2,by=names("Var1")) But always got the same message: Erro en fix.by(by.x, x) : 'by' must specify column(s) as numbers, names or logical What I'm doing wrong? Thanks, Antonio j1

#I have a data set that looks like this. A bit more complicated actually with # three factor levels but these calculations need to be done on one factor at a #I then have a set of different rates that are applied #to it. #dataset cata <- c( 1,1,6,1,1,2) catb <- c( 1,2,3,4,5,6) doga <- c(3,5,3,6,4, 0) data1 <- data.frame(cata, catb, doga) rm(cata,catb,doga) data1 # start rates #

Dear R People: Here is an interesting question(I think) Suppose I want to calculate Centered Moving Averages; i.e. x[1] <- ( sum(y[1:12]) )/12 x[2] <- ( sum(y[2:13]) )/12 and so on. Of course, this is easily done through loops. However, I have been trying to do this more elegantly, but have failed. I have tried things like j1 <- 1:109 j2 <- 12:120 x[1:109] <- ( sum( y[j1:j2])

Dear R users, I used nndist() to gain the distance of 2 nearest neighbours of the points in my dataset. Is there a way of getting the ID numbers of these nearest neighbours (along with their distances). The command I used: nn2 <- nndist(X2, k=1:2). This is the output of the nearest neighbour distances I got (the IDs of the given points are there but their IDs aren't). Any help or

I see that mksmbpasswd.sh (plus a little editing) would be a good way to set up users with "NO PASSWORD" in bulk. But suppose I don't want the risk of the "NO PASSWORD" approach. Now somebody with root access must run smbpasswd for each user they want to activate. But can't I just do this anyway (with the -a 'add user' option), without ever having run

hello: I have 3 data.frame objects. First df object: Of dim (149,31). Columns 2:31 are marked as T1..T14 and N1..N16. Name T1 T2 N1 T3 N2 N3 N4 T4 mu1 10 10 9 10 9 9 8 10 mu2 11 11 9 11 9 9 9 11 ... muN 12 12 9 11 9 9 8 12 Second df object: of Dim (50000,31). Columns 2:31 are maked as T1...T14 and N1..N16.

hello, I want to do a test for spatial correlation. I tried it with geary.test() but I don't understand the required input. x= a numeric vector the same length as the neighbours list in listw (my sampled data, I assume) listw= a listw object created for example by nb2listw (well when I check nb2listw() I get to "neighbours - an object of class nb" - but I couldn't figure