Has anyone any experience of applying observational weights in bagging? I am performing regression trees (continuous data on bird abundance) and need to account for sampling intensity. In a single tree, i.e. a call of rpart, I can specify weights either by having a separate vector called weights, or by a variable called weights in the dataframe under analysis. Both produce sensible (and identical) output. These results are different to an rpart call without a weights argument and appears to be working as expected.

However, if I analyse these data with a bagging call with a weights argument the model runs instantaneously and the output produced is empty; no error messages or warnings are generated. This happens whether the weights are within the dataframe or in a separate vector. Even assigning the weights in the bagging call (weights <-1) produces empty output. If I run the data without the weights argument I get sensible output. 

Despite being possible in rpart, are case weights not possible in bagging? I know that weights are not possible in regression under randomforests.

#this works
r1w <- rpart(how_many ~ covariates, data=ttv.data.sk, weights, method="poisson")

#this works
b1 <- bagging(how_many ~ covariates, data=ttv.data.sk, method="poisson", coob=T, nbagg=30)

#this fails
b1w <- bagging(how_many ~ covariates, data=ttv.data.sk, weights, method="poisson", coob=T, nbagg=30)

thanks in advance

Simon
____________________________________________________________
Sign-up for Bird Atlas 2007-11 at www.birdatlas.net
____________________________________________________________
Dr Simon Gillings
Senior Research Ecologist - Land Use
British Trust for Ornithology
The Nunnery, Thetford, Norfolk, IP24 2PU, UK
Tel +44(0)1842 750050 Fax +44(0)1842 750030
Charity No 216652 (England and Wales)
Company Limited by Guarantee No 357284 (England and Wales)
Registered Office The Nunnery, Thetford, Norfolk IP24 2PU
	[[alternative HTML version deleted]]

