similar to: nested random factor using lme produces errors

Hello, I would like to build a Lorenz curve and calculate a Gini coefficient in order to find how much parasites does the top 20% most infected hosts support. Here is my data set: Number of parasites per host: parasites = c(0,1,2,3,4,5,6,7,8,9,10) Number of hosts associated with each number of parasites given above: hosts = c(18,20,28,19,16,10,3,1,0,0,0) To represent the Lorenz curve: I

I have a host-parasite association matrix in which parasite species are rows and host species columns and cells contain the frequency of interactions. Some parasites are associated with many hosts, and some hosts harbor several parasites, and I want to repeatedly select only one single representative host per "generalized" (multi-host) parasite to create a new matrix in which no hosts

Hi everyone, I determined the presence of three types parasites in a passerine bird over two years. I would like to create a bar chart that shows the proportion infected on the y and year/parasite on the x such that each type of parasite is grouped together (single label) and a bar for each year . This would show if there have been changes in the prevalence of a the parasite over two years.

Hi R people! I am looking for some suggestions writing an if-else function. The idea is to characterize different plots containing counts of variables (here parasites). If a plot has a count equal or higher than 4 for any parasite the function should return a 1 else a 0. Later I can loop the function over all plots. Here I have a little subset of my data: VariablePAR Plot1

Hi, I am encountering a difficulty I don't understand. Be patient, I'm very new to analysis of variance. If I load this data: example12_7=read.table("http://msemac.redwoods.edu/~darnold/math15/data/chapter12/example12_7.dat",header=TRUE) The run the oneway.test: oneway.test(time~drug,data=example12_7,var.equal=TRUE) I get these results: data: time and drug F = 4.1881, num

Hi, I have a problem concerning discrepances between R (which I use) and Statistica (which uses my supervisor). I can't say what is the origin of these differences but unfortunately my supervisor doesn't know that either. Our response variable is number (or presence/absence) of parasites in rodents and explanatory variables are presence/absence of several alleles. The rodents were

Hi As I can't find an example of my data structure I'd like some advice on which is the most appropriate test for significant effects. If I should be using either lme or anova, is the relevant example below the best/correct way to do the test? The Data... 2 groups of patients (5 in GroupA, 7 in GroupB) 3 short acting drugs, (I'm not concerned with residual effects from the previous

Hello, Thank you very much for your help. How can I draw a Lorenz curve with several replications ? Here is an example with 4 replications: hosts=c(23,31,19,10,7,7,3, 39,40,8,3,6,2,2, 47,17,8,10,6,11,1, 30,30,10,0,15,15,0) parasites=rep(seq(from=0,to=6,by=1),4) replications=c(rep(1,7),rep(2,7),rep(3,7),rep(4,7)) test <- cbind(parasites,hosts,replications) Should I

All, I have some data on parasites on apple leaves and want to do a goodness of fit test to a Poisson distribution. This seems to do it: mites <- c(rep(0,70), rep(1,38), rep(2,17), rep(3,10), rep(4,9), rep(5,3), rep(6,2), rep(7,1)) tab <- table(mites) NSU <- length(mites) N <-

Hi all, thank you for your patience. I am dealing with a large dataset detailing patients and medications Medications are hard to code, as they are (usually) meaningless unless matched with doses. I have a dataframe with vectors (Drug1, Drug2..... Drug 16) and individual patients are represented by rows. The vectors are actually factors, with 100s of possible levels (all the drugs the patient

Hi R-users: New to R and I am trying to run a GLM with random effects. I have 3 replicates ('Replicate) of counts of parasites ('nor.tot.lep') before and after an experiment ('In.Out'). When I run lmer I get the error messages (16 of each) below... > lmer(nor.tot.lep ~ In.Out + (In.Out|Replicate),data=coho, family =tweedie(var.power = 1, + link.power = 1)) Generalized

Hi R-Users, I have 3 replicates ('Replicate) of counts of parasites ('nor.tot.lep') before and after an experiment ('In.Out'). I am trying to treat the three replicates as a random effect in order to determine if the main effect (In.Out) significantly influences my dependent variable (nor.tot.lep) after the variance explained by the replicates is accounted for. I have

I've been pouring over the documentation for dovecot, but can't find a solution to this problem. I recently took over administration of the dovecot email service at the University where I work, and things were going smoothly. We've been creating email accounts for use with JIRA, a bug reporting/tracking system, and one day recently, when I tried to add a new account to JIRA, I got

Hello everyone, I am reading a HTML table from a website with readHTMLTable() from the XML package: > library(XML) > moose = readHTMLTable("http://www.decisionmoose.com/Moosistory.html", header=FALSE, skip.rows=c(1,2), trim=TRUE)[[1]] > moose V1 V2 V3 1 07.02.2010 SWITCH to Long Bonds\n (BTTRX)

Dear all, I get an error message when I run my model and I am not sure what to do about it. I try to determine what factors influence the survival of voles. I use a mixed-model because I have several voles per site (varying from 2 to 19 voles). Here is the model: ### fm5 <-lmer(data=cdrgsaou2, alive~factor(pacut)+factor(agecamp)+factor(sex)+ResCondCorp+(1|factor(cdrgsa ou2$ids)),

Dear CentOS hive mind, I'm trying to package up a perl module into an RPM for easy deployment. I want it to be as self-contained as possible (to avoid version issues with perl modules in base or EPEL). So in my spec file, I'm doing: curl -L http://cpanmin.us | perl - App::cpanminus -L %{buildroot}/opt/zonemaster Zonemaster This way, cpanminus is installed first, and then it goes on to

Anyone here remember the old Talking Moose desktop toy from the 80's? For the unitiated, the Talking Moose was a simple applet on old Mac computers that periodically displayed an animated Bullwinkle-lookalike moose in the corner of the screen, spouting witty phrases or biting insults, as well as commenting on various activities like opening and closing programs or inserting disks. (The

Please help with this error message drugbook is an 885 x 32 dataframe >names(drugbook) [1] "DRUG1" "DRUG2" "DRUG3" "DRUG4" "DRUG5" [6] "DRUG6" "DRUG7" "DRUG8" "DRUG9" "DRUG10" [11] "DRUG11" "DRUG12"

Hello, since today I could not update my CentOS 5.3 system with yum cause of the following error message. # yum update [...] Resolving Dependencies --> Running transaction check ---> Package exiv2.i386 0:0.18.2-1.el5.rf set to be updated ---> Package perl-Params-Util.i386 0:1.00-1.el5.rf set to be updated ---> Package perl-Moose.noarch 0:0.86-1.el5.rf set to be updated -->

I have the following script (also attached): #!/usr/bin/Rscript spec=matrix(c( 'verbose', 'v', 1, "integer", 'help' , 'h', 0, "logical" ),ncol=4, byrow=TRUE) spec.dim=dim(spec) spec.opt.long=spec[,1] spec.opt.short=spec[,2] spec.opt.l <- spec.dim[1] infile <- "test.dat" args=commandArgs(TRUE); l=length(args) self =