sbaic function

Akaike's Information Criterion

Extract or modify the AIC values for models.

sbaic(x,...)
## S3 method for class 'scaleboot'
sbaic(x,k,...)
## S3 method for class 'scalebootv'
sbaic(x,...)

sbaic(x) <- value
## S3 replacement method for class 'scaleboot'
sbaic(x) <- value
## S3 replacement method for class 'scalebootv'
sbaic(x) <- value

Arguments

• x: an object used to select a method.
• k: numeric, the penalty per parameter to be used.
• value: numeric vector of AIC values for models.
• ...: further arguments passed to and from other methods.

Details

sbaic can be used to modify the aic components for models in x as shown in the examples below.

Returns

For an object of class "scaleboot", sbaic returns a numeric vector of AIC values for models. If k is missing, then the aic components in the fi vector of x are returned. If k is specified, rss-k*df is calculated for each model. For the usual AIC, k=2. For the BIC (Schwarz's Bayesian information criterion), k=log(sum(x$nb)).

References

Sakamoto, Y., Ishiguro, M., and Kitagawa G. (1986). Akaike Information Criterion Statistics. D. Reidel Publishing Company.

Author(s)

Hidetoshi Shimodaira

See Also

sbfit.

Examples

data(mam15)
a <- mam15.relltest[["t4"]] # an object of class "scaleboot"
sbaic(a) # print AIC for models
sbaic(a,k=log(sum(a$nb))) # print BIC for models
sbaic(a) <- sbaic(a,k=log(sum(a$nb))) # set BIC
sbaic(a) # print BIC for models