One row of fit statistics for every model class of the package:
logLik, AIC, BIC, df and nobs (the weight total of a weighted fit),
the dispersion parameter as dispersion with its name
(dispersion_parameter) and the direction its estimate points
(dispersion_direction; the families' parameters point different ways, so
the CPB's alpha below 1 and the gamma-count's alpha above 1 are both
underdispersion), coef_scale, the scale of the count equation's
coefficients (see tidy.cpb()), and the class's own columns (alpha for
the CPB family, family for the matched count families, n.units for the
fixed-effects fits).
Usage
# S3 method for class 'cpb'
glance(x, ...)
# S3 method for class 'cpb_fe'
glance(x, ...)
# S3 method for class 'hurdle_cpb'
glance(x, ...)
# S3 method for class 'zi_cpb'
glance(x, ...)
# S3 method for class 'gec'
glance(x, ...)
# S3 method for class 'hurdle_gec'
glance(x, ...)
# S3 method for class 'zi_gec'
glance(x, ...)
# S3 method for class 'count_reg'
glance(x, ...)
# S3 method for class 'zi_count'
glance(x, ...)
# S3 method for class 'hurdle_count'
glance(x, ...)