Model selection, stochastic complexity and badness amplification
- 9 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1999-2004
- https://doi.org/10.1109/cdc.1991.261768
Abstract
The authors present a type of predictive stochastic complexity which penalizes overparametrization more heavily than its traditional counterparts. It forms the basis for a type of model order selection method for ARMA (autoregressive moving average) processes, which performs exceptionally well, as shown by extensive simulation results.Keywords
This publication has 5 references indexed in Scilit:
- Change point detection in a stochastic complexity frameworkPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1990
- Strong Consistency of the PLS Criterion for Order Determination of Autoregressive ProcessesThe Annals of Statistics, 1989
- On a class of mixing processesStochastics and Stochastic Reports, 1989
- Adaptive Prediction by Least Squares Predictors in Stochastic Regression Models with Applications to Time SeriesThe Annals of Statistics, 1987
- Stochastic Complexity and ModelingThe Annals of Statistics, 1986