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
On the errors-in-variables problem for time series
โ Scribed by P.M Robinson
- Publisher
- Elsevier Science
- Year
- 1986
- Tongue
- English
- Weight
- 505 KB
- Volume
- 19
- Category
- Article
- ISSN
- 0047-259X
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
This paper examines and refutes a conjecture to the effect that the solution set for a general (real) static errors-in-variables problem is a finite union of sets that are described by a finite number of linear inequalities. The conjecture is disproved by detailed examination of particular errors-in
This paper studies a semi-linear errors-in-variables model of the form Y i = x$ i ;+ g(T i )+e i , X i =x i +u i (1 i n). The estimators of parameters ;, \_ 2 and of the smooth function g are derived by using the nearest neighbor-generalized least square method. Under some weak conditions, it is sho