indicates whether model weights should be calculated with AIC
or log-likelihood.
trace
if TRUE, information is printed during the running of
arm.glm.
Value
An object of class "averaging" contaning only full averaged
coefficients. See model.avg for object description.
encoding
utf-8
Details
For each of all-subsets of the global model, parameters are estimated
using randomly sampled half of the data. Log-likelihood given the remaining half
of the data is used to calculate AIC weights. This is repeated R
times and mean of the weights is used to average all-subsets parameters
estimated using complete data.
References
Yang Y. (2001) Adaptive Regression by Mixing.
Journal of the American Statistical Association 96: 574–588.
Yang Y. (2003) Regression with multiple candidate models: selecting or mixing?
Statistica Sinica 13: 783–810.
