Hi, Robert and all others



Thanks for the suggestions and directions pointed out from the community. It seems there are two packages for the work:

1. Using predict function from package "raster". The function can project a fitted model of any class that has a 'predict' method (or supplying a similar method as fun argument. E.g. glm, gam, or randomForest) to a raster object. Examples can be found in package "dismo"; and

2. Using package "Biomod", which can build, evaluate and forecast up to 8 models (e.g. Maxent, MARS, RF, etc.). However, Biomod can only handle presence/absence data (i.e. probability or abundant data need to transform to 0/1).



Thanks again for the help.



Li



-----Original Message-----
From: r-sig-ecology-bounces@r-project.org [mailto:r-sig-ecology-bounces@r-project.org] On Behalf Of Robert J. Hijmans
Sent: Thursday, 7 March 2013 10:35 AM
To: r-sig-ecology@r-project.org
Subject: Re: [R-sig-eco] Projecting model to landscape



Li,



You can use the "predict" function in the 'raster' package. There are also

examples with randomForest and other techniques in this vignette that comes

with the 'dismo' package:

http://cran.r-project.org/web/packages/dismo/vignettes/sdm.pdf



Robert







> Li Wen-2 wrote

> > Dear list member

> >

> >

> >

> > I have fitted a Random Forest model for species distribution, and want to

> > use it to project the model to a defined landscape (i.e. forecasting for

> > all

> > grids in an area) . The landscape has all the environment covariates

> > (rasters) and cover a large region (over 1000*1000 grids). I wonder if

> > there

> > is package in R to do this. Thank you for your help in advance.

> >

> >

> >

> > Cheers

> >

> > Li

> >

>



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