Hi there,
I am currently working on a project that involves climate model data stored in
a NetCDF file. I am currently trying to calculate "weighted" spatial annual
"global" averages for precipitation. I need to do this for each of the 95 years
of global precipitation data that I have. The idea
Hi Roger,
According to the book "Numerical Ecology" by Legendre&Legendre in 2012, a
progressive (sequential) Bonferroni correction is a modified version of
Bonferroni correction, where the Bonferroni-corrected level is computed for
each distance class separately instead of using a consistent level
Thanks for the information.
Drew Tyre escreveu no dia segunda, 18/03/2019 à(s) 11:48:
> I don't think the number of presences is the problem.
> "A term has fewer unique covariate combinations than specified maximum
> degrees of freedom"
> One of your covariates has a small number of unique value
Hello
I am trying to run several algorithms in biomod 2 (GLM, GAM, ANN, SRE) but
I received the following menssage.
Model=GAM
GAM_mgcv algorithm chosen
Automatic formula generation...
> GAM (mgcv) modelling...Error in
smooth.construct.tp.smooth.spec(object, dk$data, dk$kn
On Sun, 17 Mar 2019, Mingke Li wrote:
Dear list,
I am trying to generate a correlogram of Moran's I, with symbols showing if
the coefficient is significant or not after the progressive Bonferroni
correction. Now I'm using the "correlog" function in the package ncf to
calculate the coefficients
On Sun, 17 Mar 2019, Leonardo Matheus Servino wrote:
My script:
No, not your script, a *reproducible* example, using a built-in data set.
Nobody can run your code without your data, and we don't need your data.
Did you read my reply? Why have you quoted the numerical arguments - a
clear err
