On constrained maximum likelihood estimation with non-i.i.d. observations

Annals of the Institute of Statistical Mathematics

Volumn 36, Issue 1, 1984, Pages 239-249

  Crowder, Martin ^a  

^a UNIVERSITY OF SURREY   (United Kingdom)

Author keywords

AMS 1980 subject classification: Primary 62F12; asymptotic estimation theory; Constrained maximum likelihood; inequality constraints; non i.i.d. observations

Indexed keywords

EID: 51249181748     PISSN: 00203157     EISSN: 15729052     Source Type: Journal    
DOI: 10.1007/BF02481968     Document Type: Article

References (9)

1. Maximum likelihood estimation of parameters subject to restraints
2. Martingale central limit theorems
3. Maximum likelihood estimation for dependent observations
4. Least-squares fitting of a polynomial constrained to be either non-negative, non-decreasing or convex
5. Maximum likelihood estimation in non-standard conditions
6. Central limit theorems for martingales and for processes with stationary increments using a Skorokhod representation approach
7. The Lagrangian multiplier test
8. Note on the consistency of the maximum likelihood estimate