similar to: How to extract coefficients from sequential (type 1) ANOVAs using lmer and lme

I have used foreach() for parallel computing but in the current problem, it is not working. Given the volume and type of the data involved in the analysis, I will try to give below the complete code without reproducible example. In short, each R environment will draw a set of separate files, perform the analysis and dump in separate folders. splist <- c("juoc", "juos",

Dear R wizes, I have a data.frame of species abundances with column names consisting of 4 letter codes then an underscore and a number like this: abco_1, abco_2, abco_3, psm_1, psme_2, psme_3, etc. I would like to get an identifier for all the abco, and psme and other species etc. I used spec.fact<-substring(names(spec.count),1,4) To make a vector of the first 4 letters of

Your code generates an error that has nothing to do with dopar. I have no idea what your function stack is supposed to do; you may be inadvertently calling utils::stack which would produce this kind of error: > stack(1:25, RAT = FALSE) Error in data.frame(values = unlist(unname(x)), ind, stringsAsFactors = FALSE) : arguments imply differing number of rows: 25, 0 HTH, Peter On Wed, Dec 6,

I'm trying to use tapply to output means and SD or SE for my data but seem to be limited by how many times I can subset it. Here's a snippet of my data > stems353[1:10,] Time DataSource Plot Elevation Aspect Slope Type Species SizeClass Stems 1 Modern Cameron 70F221 1730 ESE 20 Conifer ABCO Class1 3 2 Modern Cameron 70F221 1730

(This time with the r-help in the recipients...) Be careful when mixing lme4 and lmerTest together -- lmerTest extends and changes the behavior of various lme4 functions. >From the help page for lme4-anova (?lme4::anova.merMod) > ?anova?: returns the sequential decomposition of the contributions > of fixed-effects terms or, for multiple arguments, model >

Please reread my point #1: the tests of the (individual) coefficients in the model summary are not the same as the ANOVA tests. There is a certain correspondence between the two (i.e. between the coding of your categorical variables and the type of sum of squares; and for a model with a single predictor, F=t^2), but they are not the same in general. The t-test in the model coefficients is simply

Hi All, I am trying to use optim() to minimize a function with a penalty function term. This is a simple model bioeconomic model of a fishery. The penalty function constrains the amount of effort (f) at 9. This works fine. The code is: ********** nfleets<-2 M<-1 M<-array(M,dim=c(nfleets)) N<-1000 cost<-c(30,30) cost<-array(cost,dim=c(nfleets)) Price<-2

Hi there, I am trying to run an MCMC on stable isotope data from certain organisms to determine their dietary habits in the package SIAR. I have prepared my data according to Inger, R., Jackson, A., Parnell, A., Bearhop, S. : SIAR V4 (Stable Isotope Analysis in R) an Ecologist's Guide (also better known as 'SIAR for dummies'), which is as follows: - consumer data table (columns

Hei, i am trying to plot the means of two variables (d13C and d15N), by 2 grouping factors (Species and Year) that i obtained by the function tapply. I would like to plot with different colours according to the Year and show the "Species" as data labels. My data looks like this: Species d13C d13N Year "Species1" 14,4 11.5 2009 "Species2"

I'm absolutely not brilliant with R yet and working with package SIAR. 1) SIAR reads the first column of a table.txt as "int" instead of "num". Who can help? 2) I therefore made tables with a data.frame() > that seems to work. But at the end of the loading proces of the SIARmodel, I get a warning screen with "Session Aborted". Everything crashes and I can start

Hello, Beginner, sorry if this is wasting anyone's time, but have been working on this for a couple of days now, think it should have take a few hours! The Problem: Error in Summary.factor(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, : max not meaningful for factors I have tried to re-arrange and check formula. I am working in SIAR, and cannot get model1 to run because of the error

I collected eggs laid by Springtails everyday over 28 days after swich to isotopically enriched diet. The eggs were pooled at day 7, 14, and 28 (+ day 0 = initial value) and analyzed for isotopes. After the diet switch the isotopic values of the adults and eggs change towards those of the new diet. Here are the d13C values (y) of the eggs: x y 0 -22.2 0 -22.2 0 -22.2 0 -22.0 7

dear R-friends, i`ve got a large dataset of vegetation-samples with about 500 variables(=species) in the following format: 1 spec1 1 spec23 1 spec54 1 spec63 2 spec1 2 spec2 2 spec253 2 spec300 2 spec423 3 spec20 3 spec88 3 spec121 3 spec200 3 spec450 . . this means: sample 1 (grassland) with the species (=spec) 1, 23, 54, 63 is it possible to get a following data-structure for further

Is there a way to create a 'bubble plot' in R? For example, if we define the following data frame containing the level of y observed for 5 patients at three time points: time<-c(rep('time 1',5),rep('time 2',5),rep('time 3',5))

Dear all, We are trying to fit a non linear model to dispersal data. It seems that sometimes when the fit of the model of the data is not very good we start getting singular gradient errors. However if we modify slightly the data this won't occurr. We have also tried changing the initial parameter values and the algorithm for fitting in nls but didn't help. So we ended up programming a