similar to: model average for GLM comparison

Hi, I am having problems trying to assess the significance of random terms in a generalized linear mixed model using lme4 package. The model describes bird species richness R along roads (offset by log length of road log_length) as a function of fixed effects Shrub (%shrub cover) and Width (width of road), and random effect Site (nested within Site Cluster). >From reading answers to previous

I have created a list of tables with the same columns but different number of row. Example (actual list has ~200 elements): > temp1<- data.frame(ID=c("Herb","Shrub"),stat=c(4,5),pvalue=c(.03,.04)) > temp2<- data.frame(ID=c("Herb","Shrub", > "Tree"),stat=c(12,15,13),pvalue=c(.2,0.4,.3)) > L<-list(a=temp1,b=temp2) > L $a

I have a function (see below). This function has one object, ID. If I run the loops by themselves using a character value (ie,"VFFF1-7") instead of the function object, then the loops work fine. However, when I try to insert the character value via the function call, it doesn't work. I don't get an error, but the TotalCover.df dataframe does not update according to the loop

I have a function (see below). This function has one object, ID. If I run the loops by itself using a character value (ie,"VFFF1-7"), then the loops work fine. However, when I try to insert the character value via the function call, it doesn't work. I don't get an error, but the TotalCover.df dataframe does not update according to the loop criteria. Any obvious problems that

Hi Helpers: I have a factor object that has 314k entries of 39 land cover types. (This object can be coerced to characters neatly should that be easier to work with.) > length(foo) [1] 314482 > foo[1:10] [1] Montane Chaparral Barren Red Fir Red Fir [5] Red Fir Red Fir Red Fir Red Fir [9] Red Fir Red Fir 39 Levels:

Hopefully the attachment will make it this time... Hi: I am practicing with the attached shapefile and was wondering if I can get some help. Haven't used 'rgdal' and 'maptools' much but it appears to be a great way bring map data into R. Please take a look at the comments and let me know if I need to explain better what I am trying to accomplish. library(rgdal)

The shapefile data can be downloaded from the link below: download all the six files and save them on your working directory and make sure the dsn path is set to where the files are saved. My shapefiles are saved on C:/Data. https://secure.filesanywhere.com/fs/v.aspx?v=897263875a6472a99baa Hi: I am practicing with the attached shapefile and was wondering if I can? get some help. Haven't

Hi: I am using a subset of the below dataset to predict PRED_SUIT for the whole dataset but I am having trouble with 'newdata'. The model was created with 153 records and want to predict for 208 records. wolf2 <- structure(list(gridcell = c(367L, 444L, 533L, 587L, 598L, 609L, 620L, 629L, 641L, 651L, 662L, 674L, 684L, 695L, 738L, 748L, 804L, 805L, 872L, 919L, 929L, 938L, 950L, 958L,

Dear All I have a problem with the height of the boxes in the key in the following. (The text is over 2 lines to accentuate the problem of no space between the rectangles.) Is there an easy way to put a space between the rectangles; size controls the width but there appears to be nothing for the height? xyplot(1~1, key = list(corner = c(0.8,0.8),

Dear R-helpers, I have a time series analysis problem in R: I want to analyse the output of my simulation model which is proportional cover of shrubs in a savanna plot for each of 500 successive years. I have run the model (which includes stochasticity, especially in the initial conditions) 17 times generating 17 time series of shrub cover. I am interested in a possible periodicity of shrub

Hi Folks, I have repeated measures for data on association time (under 2 acoustic condtions) in male and female frogs as they grow to adulthood (6 timepoints). Thus, two within-subject variables (Acoustic Condition: 2 levels, Timepoint: 6 levels) and one between-subject variable (Sex:male or female). I am pretty sure my distributions depart from normality but I would first like to simply run a

Hello all, This may be a simple question to answer, but I'm a little bit stumped with respect to the calculation of the F statistics in nested anovas with unbalanced design in R. In my case, I have 11 vegetation transects (with 1000 10cmx10cm squares), where we estimated shrub cover. We have two different treatments: wildfire (4 transects) and prescribed burning (7 transects) and we want to

mathias dufresne schreef op 12-07-2016 13:39: > Hi, > > Let me try to re-formulate, please tell me if I'm wrong. > > You have a bunch of users declared locally in /etc/passwd or something > like that on one system. > > Now you would like to have another system using this users list with > Samba. > You also want these users to be valid only as long as the share

If I try: rsync -lptgoD -e "ssh -i /root/.ssh/rsync-key" --verbose --exclude="/*.*" --exclude="*.xml" --include="+ */Tariff/" 192.168.1.1:/home/e-smith/files/ibays/frogs/files/dbs/ rsync lists the correct files, but if I add the destination like this: rsync -lptgoD -e "ssh -i /root/.ssh/rsync-key" --verbose --exclude="/*.*"

I am basically trying to append a value(vector) to one dataframe using a relational value from another dataframe. Obviously, I can use a loop to accomplish this. However, is there a way to vectorize it? Example: > data <- data.frame(c(1,1,1,2,2,2,3,3,3),rep(2,9)); names(data) <- > c("Sample","Score") > meta <-

I expect to release Ogg Frog 1.0 for public alpha test on Saturday, August 12. The date might slip a little depending on how my current job hunt goes; if I get a job sooner than I expect, I'll have to cut back on my development which has been full-time for a while now. The planned features are detailed at the page where the downloads will eventually be found:

I expect to release Ogg Frog 1.0 for public alpha test on Saturday, August 12. The date might slip a little depending on how my current job hunt goes; if I get a job sooner than I expect, I'll have to cut back on my development which has been full-time for a while now. The planned features are detailed at the page where the downloads will eventually be found:

Dear WizaRds, unfortunately, I have been unable to replace the '99' and '999' entries in library(UsingR) attach(babies) as definitions for missing values NA, because sometimes the 99 entry is indeed a correct value. Usually, or so I thought, NAs can easily replace a, say, 999 entry via mymat[mymat==999] <- "yodl" in a matrix or data frame. Alas, the babies'

Hello all, I have a data set where the response variable is the percent cover of a specific plant (represented in cover classes 0,1,2,3,4,5, or 6). This data set has a lot of zeros (plots where the plant was not present). I am trying to model cover class of the plant as a function of both total nitrogen and shrub cover. After quite a bit of research I have come across a conditional approach

I have fitted the faults.data to glm.nb and to the function negbin from the package aod. The output of both is the following: summary(glm.nb(n~ll, data=faults)) Call: glm.nb(formula = n ~ ll, data = faults, init.theta = 8.667407437, link = log) Deviance Residuals: Min 1Q Median 3Q Max -2.0470 -0.7815 -0.1723 0.4275 2.0896 Coefficients: