Interactive maximum likelihood estimation

Autor:	D. L. Prager, Peter E. Wellstead
Rok vydání:	1980
Předmět:	Mathematical optimization Control and Systems Engineering Restricted maximum likelihood Estimation theory Expectation–maximization algorithm M-estimator Maximum likelihood sequence estimation Likelihood function Likelihood principle Marginal likelihood Computer Science Applications Mathematics
Zdroj:	International Journal of Control. 32:1005-1030
ISSN:	1366-5820 0020-7179
Popis:	This paper describes an approach to maximum likelihood estimation which is based upon recursive hypothesis testing. The advantage of the method over existing hill-climbing and approximate recursive methods lies in the degree of information which can be obtained from the algorithm. In particular, cross-sections through the loss function are provided in a graphical form. This allows the analyst to see the likelihood function evolve, and make subjective decisions based upon this information. Effectively, the method computes all the relevant points on the loss function surface, making the technique ideal for short data runs where conditioning of the likelihood function is a problem. The method compares favourably with alternative maximum Likelihood algorithms in terms of computational effort and has none of their convergence problems.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::6b4698fc9437d8e6f225c99f2c0f0746 https://doi.org/10.1080/00207178008922904 Zobrazit plný text záznamu