similar to: nlme error on dimensions in multiplication

I have a set of data frames ds1, ds2, ... each having the same columns and column names: ds1 <- data.frame(x=c(1,2,3,4), y=c(5,6,7,8)) ds1 <- data.frame(x=c(9,10,11,12), y=c(13,14,15,16)) ... and I would like to combine them into just one data frame like ds <- rbind(ds1, ds2, ...) Because there are so many of them, I will have to use a character array nms <-

I was wondering if someone can help me figure out the following: I have two patient datasets, ds1 and ds2. ds1 has fields "patid", "date", and "lab1". ds2 has "patid", "date", and "lab2". I want to find all the patids that have at least 2 dated records for each lab. I started by splitting each dataset by patid, to create ds1.list

I am just starting to code in R and need some help as I am used to doing this in SAS. I have a dataset that looks like this: Chemical Well1 Well2 Well3 Well4 BOD 13.2 14.2 15.5 14.2 O2 7.8 2.6 3.5 2.4 TURB 10.2 14.6 18.5 17.3 and so on with more chemicals.... I would like to transpose my data so that it looks like this: Chemical WellID Value BOD Well1 13.2 BOD Well2 14.2 BOD Well3 15.5 BOD

Hi, I was taken off guard by the following behavior in a lattice plot. I frequently want to add a predicted curve defined at more points than in the formula expression of xyplot. There have been numerous examples of how to do this on r-help, but I still often struggle to make this work. I just realized that specifying one of the axes on a log scale does not guarantee that the added data for a

I''m seeing some pretty pitiful performance using ZFS on a NFS server, with a ZFS volume exported (only with rw=host.foo.com,root=host.foo.com opts) and mounted on a Linux host running kernel 2.4.31. This linux kernel I''m working with is limited in that I can only do NFSv2 mounts... irregardless of that aspect, I''m sure something''s amiss. I mounted the zfs-based

Dear all, I have a multiline plot with each line labeled with a different letter. But I'm not able to make the legend display the same kind of pattern '-a-', instead the letter is overwritten by the line. A simpler legend with only the letter is not very visible and the pt.bg does nothing with letters. Any idea? plot(1:10,10:1,lty=1,type='b', lwd=2,pch='a')

Dear R experts, Wish you all a HAPPY NEW YEAR! How do I go about plotting (using lattice) overlays of an ID (group=ID) observed, fitted data in each panel of a multiple panel plot (each panel identified by DS1 + DS2 + DS3)? "x" variable is X1 in the accompanying section of a dataset. each individual is identified by color and Y's are identified by "pch" or "lty".

Hi! All, I am trying to fetch rows from a data frame which matches to first 2 columns of another data frame. Here is the example what I am trying to do: > ptable=read.table(file="All.txt",header=T,sep="\t") > ptable=as.matrix(ptable) > dim(ptable) [1] 9275 6 > head(ptable) Gene1 Gene2 PCC PCC3 PCC23 PCC123 [1,]

Hope one of you could help with the following question/problem: We would like to explain the spatial distribution of juvenile fish. We have 2135 records, from 75 vessels (code_tripnr) and 7 to 39 observations for each vessel, hence the random effect for code_tripnr. The offset (‘offsetter’) accounts for the haul duration and sub sampling factor. There are no extreme outliers in lat/lon. The model

Dear R users, I have a problem with reshaping data. I know such questions have been asked before, but I can't get it right, neither with the reshape function nor with the melt function. My dataset has about 407 variables and about 48000 cases. Each case looks as follows: V1 v2 v3 v4 v5 v6 v7 x1 y1 x2 y2 .... x200 y200 V1 is unique, v2-v7 are

Hello, I'm pretty new to R. Basically, how do I speed up the for loop below. Or better yet, get rid of the for loop all together. objective: plot two data sets column against column by index. These data sets have alot NA's. Some columns are all NA's. I need the plots to overlay. I don't like the plots in matplot(). Needs to be much faster than the code below... #simple sample

I am trying to run a GLMM on some binomial data. My fixed factors include 2 dichotomous variables, day, and distance. When I run the model: modelA<-glmmPQL(Leaving~Trial*Day*Dist,random=~1|Indiv,family="binomial") I get the error: iteration 1 Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 >From looking at previous help

Hi, We have data of two groups of subjects: 32 elderly, 14 young adults. for each subject we have 15 observations, each observation consisting of a reaction-time measure (RT) and an activation maesure (betadlpcv). since we want to analyze the influence of (age-)group and RT on the activation, we call: lme(betadlpcv ~ RT*group, data=our.data, random=~ RT |subject) this yields: Error in

I am running a two-node web cluster on OCFS2 via DRBD Primary/Primary (v8.3.8) and Pacemaker. Everything seems to be working great, except during testing of hard-boot scenarios. Whenever I hard-boot one of the nodes, the other node is successfully fenced and marked ?Outdated? * <resource minor="0" cs="WFConnection" ro1="Primary" ro2="Unknown"

https://bugs.freedesktop.org/show_bug.cgi?id=48742 Bug #: 48742 Summary: fbotexture -arb misrenders on nv43 Classification: Unclassified Product: Mesa Version: git Platform: x86 (IA32) OS/Version: Linux (All) Status: NEW Severity: normal Priority: medium Component: Drivers/DRI/nouveau

Hello all, After setting up a Solaris 10 machine with ZFS as the new NFS server, I''m stumped by some serious performance problems. Here are the (admittedly long) details (also noted at http://www.netmeister.org/blog/): The machine in question is a dual-amd64 box with 2GB RAM and two broadcom gigabit NICs. The OS is Solaris 10 6/06 and the filesystem consists of a single zpool stripe

Hello, I am trying to design new variance structures by using fixed effects variables in combination with the VarPower function. That is, I would like to create and evaluate my own variance function in the data frame and then incorporate it into the model using varPower, with value=.5. As a start, I am trying to recreate the function of VarConstPower by introducing two new variables in the

Dear R-ers, I am having trouble understanding why I am getting an error using glmmPQL (library MASS). I am getting the following error: iteration 1 Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 The long story: I have data from an experiment on pairwise comparisons between 3 treatments (a, b, c). So a typical run of an experiment

Can anyone shed any light on this? > doubt.demographic.pql<-glmmPQL(random = ~ 1 | groupid/participantid, + fixed = r.info.doubt ~ + realage + minority + female + education + income + scenario, + data = fgdata.df[coded.resource,], + na.action=na.omit, +

Dear R users, I'm attempting to fit a GLM with random effects using the tweedie family for the error structure. I'm getting the error: iteration 1 Error in logLik.reStruct(object, conLin) : NA/NaN/Inf in foreign function call (arg 3) I'm running V2.1.0 I notice from searching the lists that the same error was reported in May 2004 by Spencer Graves, but no-one was able to