ICtab {bbmle} | R Documentation |
Computes information criteria for a series of models, optionally giving information about weights, differences between ICs, etc.
ICtab(..., type=c("AIC","BIC","AICc"), weights = FALSE, delta = FALSE, sort = FALSE, nobs, dispersion = 1, mnames, k = 2) AICtab(...) BICtab(...) AICctab(...) ## S3 method for class 'ICtab': print(x,...)
... |
a list of (logLik or?) mle objects; in the case of
AICtab etc., could also include other arguments to ICtab |
type |
specify information criterion to use |
weights |
(logical) compute IC weights? |
delta |
(logical) compute differences among ICs? |
sort |
(logical) sort ICs in increasing order? |
nobs |
(logical) number of observations: required for
type="BIC" or type="AICc" unless objects have
an "nobs" attribute |
dispersion |
(stub) overdispersion estimate, for computing qAIC |
mnames |
names for table rows: defaults to names of objects passed |
k |
penalty term (largely unused) |
x |
an ICtab object |
A data frame containing:
IC |
information criterion |
df |
degrees of freedom/number of parameters |
dIC |
difference in IC from minimum-IC model |
weights |
exp(-dIC/2)/sum(exp(-dIC/2)) |
The print method uses sensible defaults; all ICs are rounded
to the nearest 0.1, and IC weights are printed using
format.pval
to print an inequality for
values <0.001
Ben Bolker
Burnham and Anderson 2002