A MIXING LIMIT THEOREM FOR LEAST SQUARES ESTIMATES IN STOCHASTIC REGRESSION MODELS

Articles in the same Issue

1. INADMISSIBILITY OF THE BEST EQUIVARIANT ESTIMATORS OF THE VARIANCE-COVARIANCE MATRIX, THE PRECISION MATRIX, AND THE GENERALIZED VARIANCE UNDER ENTROPY LOSS
2. GAMMA-MINIMAX ESTIMATION OF A BINOMIAL PROBABILITY UNDER SQUARED ERROR LOSS
3. ESTIMATION OF DISTRIBUTION FUNCTIONS UNDER ORDER RESTRICTIONS
4. MINIMAX LINEAR ESTIMATION OF THE TREND PARAMETER IN RANDOM FIELDS
5. MINIMAX SEQUENTIAL ESTIMATION IN RANDOM FIELDS APPLICATION TO THE ORNSTEIN-UHLENBECK CASE
6. A BAYESIAN RISK-CONCEPT AND OPTIMALITY CONDITIONS FOR CONFIDENCE REGIONS
7. FURTHER PARADOXES IN ADMISSIBILITY - PART II
8. ROBUST REGRESSION ESTIMATORS AND THEIR LEAST FAVORABLE CONTAMINATION CURVES
9. A MIXING LIMIT THEOREM FOR LEAST SQUARES ESTIMATES IN STOCHASTIC REGRESSION MODELS
10. GENERALIZED ESTIMATORS: A BAYESIAN DECISION-THEORETIC VIEW
11. CONSISTENCY OF THE BOOTSTRAP
12. ON THE DISTANCE BETWEEN MIXED POISSON AND POISSON DISTRIBUTIONS
13. GOODNESS OF FIT TESTS IN METRIC SPACES BASED ON BALLS AROUND THE SAMPLE
14. Book Reviews
15. Referees of volume 5 (1987)
16. Author Index of Volume 5
17. INSTRUCTIONS TO AUTHORS
18. Impressum
19. Index of Volume 5 (1987)