Description Usage Arguments Details Value Author(s) References See Also Examples
Calculate the relative log-likehood between two models.
1 |
x,y |
Fitted model objects for which there exists a |
method |
Whether to base the comparison on |
ndigits |
An integer denoting the number of decimal digits in the output. |
... |
Further arguments to pass to |
The relative log-likelihood is calculated as exp((abs(AIC(x) - AIC(y)))/2)
or exp((abs(BIC(x) - BIC(y)))/2)
, depending on the method.
You can find information regarding differences between AIC and BIC from http://methodology.psu.edu/eresources/ask/sp07
.
A vector with values:
AIC(x), BIC(x) |
The |
AIC(y), BIC(y) |
The |
relLik |
The relative likelihood between the two models. Model |
Antoine Tremblay, Statistics Canada, trea26@gmail.com
On AIC and relative log-likelihood (which they call evidence ratio):
Symonds, M.R.E and Moussalli, A. (2011). A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike's information criterion. Behavioral Ecology and Sociobiology, 65, 13–21. doi: 10.1007/s00265-010-1037-6
1 | # see example in LMERConvenienceFunctions help page.
|
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