search for: boboh

...rtals. Could someone explain how to do this? Bob -- Bob O'Hara Biodiversity and Climate Research Centre Senckenberganlage 25 D-60325 Frankfurt am Main, Germany Tel: +49 69 798 40216 Mobile: +49 1515 888 5440 WWW: http://www.RNI.Helsinki.FI/~boh/ Blog: http://network.nature.com/blogs/user/boboh Google Wave: rni.boh@googlewave.com Journal of Negative Results - EEB: www.jnr-eeb.org [[alternative HTML version deleted]]

Does anyone know of example r-code/packages for carrying out analysis? Preferably this would have examples from real experimental data of two or more competing species... Thanks Chris Buddenhagen [[alternative HTML version deleted]]

I am executing the following loops in R 15.1.0 and the first one works and produces results. However, the second one is not with initiating the object as x[i]. Further, I was able to get the second loop work in R 15.0. Am I missing something here? for(i in 1:length(b)) {y[i]<-paste(a,b[i],c,sep="") print(y[i]) print(fromJSON(file=y[i],method="C")) } for(i in 1:length(b))

(Using BRugs 0.7-5, R 2.14.2 32-bit on 64-bit Windows 7, OpenBUGS 3.2.1) 1. BRugs crashes R for me as follows. Sorry about the lack of detail; please let me know if / how to supply a more useful bug report on this issue. fit <- BRugsFit(...) # BRugs and OpenBUGS runs fine, the parameter estimates are reasonable # across 3 chains samplesBgr("beta") # crash

Dear users, I'm trying to get a dot plot but always end up with a boxplot. Can someone please tell me what I am doing wrong? df <- structure(list(FACETTE = structure(c(1L, 1L, 1L, 1L, 2L, 2L, + 2L, 2L), .Label = c("base", "tip"), class = "factor"), Sq = c(274836, + 0.74182, 0.709205, 0.984552, 279869, 255712, 26566, 301464)), .Names = c("FACETTE",

I try to do a test for dirichlet process for Multivariate normal, but Winbugs always says "expected multivariate node", does that mean I miss something at initialization? I will really appreciate the help to solve this problem Here is the R code, and Winbugs code. model { for(i in 1:N){ y[i,1:2] ~ dmnorm(mu[i,],tau[i,,]) S[i] ~ dcat(pi[]) mu[i,1:2] <- mu.star[S[i],]

Hi. I am new here, and I am writing this Winbugs code with BRugs. n=length(bi.bmi) Lagegp=13 Lgen=2 Lrace=5 Lstra=15 Lpsu=2 #model gen x race bi.bmi.model=function(){ # likelihood for (i in 1:n){ bi.bmi[i]~ dbern(p[i]) logit(p[i])<- a0 + a1[agegp[i]]+a2[gen[i]]+a3[race[i]] + a12[agegp[i], gen[i]] + gam[stra[i]]+ u[psu[i],stra[i]] } # constraints for a1, a2, a3, a12 a1[1]<-0.0

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)#

Hi, I have a simple task I can't figure out. I'd like to take some measurements I made, e.g.: year (y-axis) 1 2 3 4 5 6 counts (x-axis) 10 10 20 30 40 50 And then, make a barplot with the x-axis ticks (representing the borders between years) between the bars. However, barplot seems to force you to make the x-axis arbitrary categories. I want it to be continuous (as in a