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Asymptotic properties of projections with applications to stochastic regression problems
- Source :
- Journal of Multivariate Analysis. (3):346-370
- Publisher :
- Published by Elsevier Inc.
-
Abstract
- Almost sure convergence properties of least-squares estimates in stochastic regression models and an asymptotic theory of related Euclidean projections are developed herein. Applications to autoregressive processes and to dynamic input-output systems are also discussed.
- Subjects :
- Statistics and Probability
Mathematical optimization
Asymptotic analysis
Numerical Analysis
projections
Stochastic regressors
Strong consistency
Regression analysis
dynamic models
Dynamic models
Convergence of random variables
Autoregressive model
martingales
minimum eigenvalue
Euclidean geometry
Applied mathematics
strong consistency
Statistics, Probability and Uncertainty
Regression problems
autoregressive processes
Mathematics
least squares estimates
Subjects
Details
- Language :
- English
- ISSN :
- 0047259X
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Journal of Multivariate Analysis
- Accession number :
- edsair.doi.dedup.....00bc0564cbcee3283c0d5019b0a7e86c
- Full Text :
- https://doi.org/10.1016/0047-259X(82)90071-9