Hello,
I have little experience using the raster package and I am currently trying to develop a predicted surface based on a gradient boosted model (gbm package).
The basic steps I am using include the following:
# Creating a raster stack of independent variables
USHGT <- raster("ushgt.asc", package="raster")
... (other variables omitted for post)
ras_stk <- stack(USHGT, HYELB, T1TO5LE, URBD_D, SG_UNIT, MINTEMP, ANNPCP, TC_B04, TC_B07)
# Create the prediction model
... I am using a separate script that creates the gbm object and due to the length I will not include. The outcome is a gbm object.
.. Now I use the following, which fails:
r <- predict(ras_stk, myData, filename=OutFile, na.rm=TRUE, overwrite=TRUE, n.trees=myData$n.trees, type="response", progress="window")
Error:
Error in model.frame.default(terms(reformulate(object$var.names)), newdata, :object is not a matrix
The raster package manual states that the predict function will work on any model that a predict method has been implemented.
Does anyone have experience with this or possibly an idea on how I might solve the issue.
Thank you,
mike
raster package and predict for GBM models
3 messages · Robert J. Hijmans, Michael ODonnell
Hi Mike, I cannot know from what you send, but the second argument should be your gbm object, and from your name "myData" I am guessing it is not (unless it really is referring to youModel). One of the two vignettes of the 'dismo' package is about 'gbm' (boosted regression trees) and 'raster' . So in principle it should work. Robert
On Thu, Nov 4, 2010 at 7:34 AM, Michael ODonnell <odonnems at yahoo.com> wrote:
Hello,
I have little experience using the raster package and I am currently trying to develop a predicted surface based on a gradient boosted model (gbm package).
The basic steps I am using include the following:
# Creating a raster stack of independent variables
USHGT <- raster("ushgt.asc", package="raster")
... (other variables omitted for post)
ras_stk <- stack(USHGT, HYELB, T1TO5LE, URBD_D, SG_UNIT, MINTEMP, ANNPCP, TC_B04, TC_B07)
# Create the prediction model
... I am using a separate script that creates the gbm object and due to the length I will not include. The outcome is a gbm object.
.. Now I use the following, which fails:
r <- predict(ras_stk, myData, filename=OutFile, na.rm=TRUE, overwrite=TRUE, n.trees=myData$n.trees, type="response", progress="window")
Error:
Error in model.frame.default(terms(reformulate(object$var.names)), newdata, ?:object is not a matrix
The raster package manual states that the predict function will work on any model that a predict method has been implemented.
Does anyone have experience with this or possibly an idea on how I might solve the issue.
Thank you,
mike
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Robert, sorry. Yes, myData is my gbm object. Also, I figured out what I had done wrong. The raster stack I created specified a data set name that was lowercase and the the gbm model was specifying upper case for the same raster layer. Once I use the correct name, it worked. Thank you for the response. Mike
--- On Thu, 11/4/10, Robert J. Hijmans <r.hijmans at gmail.com> wrote:
From: Robert J. Hijmans <r.hijmans at gmail.com> Subject: Re: [R-sig-Geo] raster package and predict for GBM models To: "Michael ODonnell" <odonnems at yahoo.com> Cc: r-sig-geo at stat.math.ethz.ch Date: Thursday, November 4, 2010, 10:58 AM Hi Mike, I cannot know from what you send, but the second argument should be your gbm object, and from your name "myData" I am guessing it is not (unless it really is referring to youModel). One of the two vignettes of the 'dismo' package is about 'gbm' (boosted regression trees) and 'raster' . So in principle it should work. Robert On Thu, Nov 4, 2010 at 7:34 AM, Michael ODonnell <odonnems at yahoo.com> wrote:
Hello, I have little experience using the raster package and
I am currently trying to develop a predicted surface based on a gradient boosted model (gbm package).
The basic steps I am using include the following:
# Creating a raster stack of independent variables
USHGT <- raster("ushgt.asc", package="raster")
... (other variables omitted for post)
ras_stk <- stack(USHGT, HYELB, T1TO5LE, URBD_D,
SG_UNIT, MINTEMP, ANNPCP, TC_B04, TC_B07)
# Create the prediction model ... I am using a separate script that creates the gbm
object and due to the length I will not include. The outcome is a gbm object.
.. Now I use the following, which fails: r <- predict(ras_stk, myData, filename=OutFile,
na.rm=TRUE, overwrite=TRUE, n.trees=myData$n.trees, type="response", progress="window")
Error: Error in
model.frame.default(terms(reformulate(object$var.names)), newdata, ?:object is not a matrix
The raster package manual states that the predict
function will work on any model that a predict method has been implemented.
Does anyone have experience with this or possibly an
idea on how I might solve the issue.
Thank you, mike
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