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Sounds like you are looking for meta-analysis. But I'm not 100% sure about this. Cheers! On Fri, 11 Jan 2019 at 19:57, Roy Averill-Murray <royaverillmurray at gmail.com> wrote: > How does one estimate beta parameters and...

Hi Bruce, Sounds like that you are looking for sp:::over(). HTH, Torsten On Wed, 20 Feb 2019 at 16:20, Bruce Miller <batsncats at gmail.com> wrote: > Hi all, > Back in January I inquired about R packages to extract...

Dear list members, I' m fitting a multivariate time series using mgcv:::gamm. I cannot run a summary on my fitted object and no gam.check(). Any idea how I can assess the model fit and diagnostic plots? Because I...

Hi Irene, I'm not sure whether I understand your aim completely. It sounds similar to stratigraphically constrained clustering (CONISS) - an approach often used in paleoecology and implemented in the packages rioja and adjclust. Instead of stratigraphy/age you could...

Hi, I can't try it but maybe you need a vector with all factorial predictors. Hence, put them all in c(). me <- maxent(predictors, occtrain, factors=c("bion","morfo", "sed")) On Tue, Sep 22, 2020 at 10:08 AM...

"adonis2(speciesdataset~A*B, by="margin") but then only the effect of the interaction is tested." This is not entirely correct. adonis2(speciesdataset~A:B, by="margin") would test the interaction alone. ~A*B unfolds to ~A+B+A:B...

Hi Mike, not sure whether I understand what you mean with Word 7 (2007?). Do you copy and paste the figure or do you export it with a function like tiff() or pdf()? In the first case, this is maybe...

(sorry, I forgot to include the list) Hi, My guess is that the problem is not the size of the phylogeny but the dimension of the community matrix. How many localities and species per locality do you have? Does it...

Bayesian mixed models implemented in MCMCglmm and brms have an argument to specify the variances for meta analysis. I never used them for this task, though. However, the author of brms is psychologist where meta analyses are common. Cheers! On...

Hi Fernando, using a PCoA for variation partitioning should be possible. This should equal a distance-based redundancy analysis (plus some magic to make the PCoA euclidean). I don't know ade4 very well but alternatively you could use the...

Dear list, My apologies if this question doesn't fit the scope of the mailing list. I try to solve some differential equations with the deSolve::ode and need to feed some values at certain time-points into the equations...

What went wrong when following this manual for installing Rstan? https://github.com/stan-dev/rstan/wiki/Installing-RStan-from-source-on-a-Mac On Thu, Sep 10, 2020 at 10:02 AM Thierry Onkelinx via R-sig-mixed-models...

Hi, In general, you can create a list containing matrices, data.frames, or (almost) any object in the following way: # 2 Matrices as example M1 <- matrix(NA, ncol = 5, nrow = 3) M2 <- matrix(NA, ncol = 3, nrow = 5) List <- list...

I see. Thanks for explaining Jari! On Tue, 16 Oct 2018 at 14:54, Jari Oksanen <jari.oksanen at oulu.fi> wrote: > > > On 16/10/18 11:23, Torsten Hauffe wrote: > > "adonis2(speciesdataset~A*B, by="margin") but then only...

What is happening when you changeyour sample_prior = "yes" in brm() back to the default "no"? (Disclaimer: From the brm help, I only understand the settings "no" and "only" sampling the prior). Cheers! On Fri, Apr 16, 2021 at 12...

Great! Having a machine with 120 GB of RAM (*envy*), you can certainly use parallelization to boost the turnover calculation. Cheers! On Tue, Mar 10, 2020 at 5:40 PM Jens Ringelberg <jens.ringelberg at gmail.com> wrote: > Hi Torsten...

Hi, What is the output of class(my_data$Sampling)? If it is not factor (but character), you could write my_data$Sampling <- as.factor(my_data$Sampling) Then levels(my_data$Sampling) should return Sep18 etc. Cheers! On Tue...

The boral package features a straight-forward coding of nested 'random' row effects. If I remember right, the help package includes an 2-level nested example. boral uses Bayesian inferrence and not permutations and is therefore closer to mvabund than...

Hi Alexandre, looks like you are trying to apply inverse distance weighting with gstat. For that your command should be something like this: Model_ok <- gstat( id='NMDS1_kri', formula= NMDS1 ~ 1 , data = X) Where X is a data.frame...

Hi, you may have a look to the following publication: http://onlinelibrary.wiley.com/doi/10.1111/1365-2656.12362/abstract Barwell et al. 2015 nicely compare the characteristics of different pairwise beta-diversity measures. They give recommendations for choosing...