Under minimum assumptions on the stochastic regressors, strong consistency of Bayes estimates is established in stochastic regression models in two cases: (1) When the prior distribution is discrete, the p.d.f. f of i.i.d. random errors is assumed to have finite Fisher information I= & ( f $) 2 รf
โฆ LIBER โฆ
Strong Consistency in Stochastic Regression Models Via Posterior Covariance Matrices
โ Scribed by Inchi Hu
- Book ID
- 124300009
- Publisher
- Oxford University Press
- Year
- 1997
- Tongue
- English
- Weight
- 585 KB
- Volume
- 84
- Category
- Article
- ISSN
- 0006-3444
- DOI
- 10.2307/2337595
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