Multistep prediction error methods for linear time series models are considered from both a theoretical and a practical standpoint. The emphasis is on autoregressive moving-average (ARMA) models for which a multistep prediction error estimation method (PEM) is developed. The results of a Monte Carlo
Prediction error methods for limit cycle data
✍ Scribed by Raúl A. Casas; Robert R. Bitmead; Clas A. Jacobson; C.Richard Johnson Jr.
- Book ID
- 108307253
- Publisher
- Elsevier Science
- Year
- 2002
- Tongue
- English
- Weight
- 212 KB
- Volume
- 38
- Category
- Article
- ISSN
- 0005-1098
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
This paper introduces the idea of predicting 'designer error' by evaluating devices using Human Error Identification (HEI) techniques. This is demonstrated using Systematic Human Error Reduction and Prediction Approach (SHERPA) and Task Analysis For Error Identification (TAFEI) to evaluate a vending
A new form of prediction error method (PEM) is developed. It is applicable to the case where the model structure of interest can be imbedded in a larger model structure whose estimation is relatively easy. An optimal way of reducing the larger model to the smaller model structure is presented and va