Dear R users,
I am using package "MuMIn" to conduct model average and prediction (GLMM
models), and I got full average and conditional average. What I am interested
in is the results of conditional average, but it seems the function
"predict.averaging" in package "MuMIn" cannot use conditional average to make
prediction for GLMM models:
"If all the component models are oridinary linear models, the prediction can
be made either with the full averaged coefficients (the argument full = TRUE
this is the default) or subset-averaged coefficients. Otherwise the prediction
is obtained by calling predict on each component model and weighted averaging
the results, which corresponds to the assumption that all predictors are
present in all models, but those not estimated are equal zero (see ��Note�� in
model.avg)".
Do anyone know how to make prediction by conditional average, but not full
average. Any help will be appreciated, many thanks.
Best,
Yong Shen
--
Yong Shen
Professional Research Series Position
Sun Yat-Sen University, Guangzhou, P.R. China
winnie56...@163.com
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