`BIC,rateReg-method`

is an S4 class method calculating
Bayesian information criterion (BIC) or so-called
Schwarz's Bayesian criterion (SBC)
for one or several `rateReg`

objects,
according to the formula
- 2 * log-likelihood + ln(nObs) * nPar,
where nPar represents the number of parameters in the fitted model
and nObs is the number of observations.

## Usage

```
# S4 method for rateReg
BIC(object, ...)
```

## Value

If just one object is provided, a numeric value representing
calculated BIC.
If multiple objects are provided, a data frame with rows
corresponding to the objects and columns `df`

and `BIC`

,
where `df`

means degree of freedom,
which is the number of parameters in the fitted model.

## Details

When comparing models fitted by maximum likelihood to the same
data, the smaller the BIC, the better the fit.
`help(BIC, stats)`

for other details.

## See also

`rateReg`

for model fitting;
`summary,rateReg-method`

for summary of a fitted model;
`AIC,rateReg-method`

for AIC.