On Uncertainty Classes and Minimax Estimation in the Linear Regression Models with Heteroscedasticity and Correlated Errors

• Authors: Grzybowski, Andrzej

Abstracts

EN

The problem of minimax estimation in the linear regression model is considered under the assumption that a prior information about the regression parameter and the covariance matrix of random component (error) is available for the decision-maker. Two models of the uncertainty of the prior knowledge (so called uncertainly classes) are proposed. The first one may represent the problem of estimation for heteroscedastic model, the other may reflect the uncertainty connected with the presence of the correlation among errors. Minimax estimators for considered classes are obtained. Some numerical examples are discussed as well.

• Publisher: Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
• Journal: Acta Universitatis Lodziensis. Folia Oeconomica
• Year: 2000
• Volume: 152

Dates

published

2000

Contributors

author

Grzybowski, Andrzej

other

Technical University of Częstochowa, Chair of Applied Mathematics

Identifiers

URI

http://hdl.handle.net/11089/19377