Strong consistency of least-squares estimates in regression models
AUTOR(ES)
Lai, T. L.
RESUMO
A general theorem on the limiting behavior of certain weighted sums of i.i.d. random variables is obtained. This theorem is then applied to prove the strong consistency of least-squares estimates in linear and nonlinear regression models with i.i.d. errors under minimal assumptions on the design and weak moment conditions on the errors.
ACESSO AO ARTIGO
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=431237Documentos Relacionados
- Strong consistency of least squares estimates in multiple regression
- A Generalized Least-Squares Estimate for the Origin of Sporophytic Self-Incompatibility
- Valuation of american interest rate options by the least-squares Monte Carlo method
- A comparative study between least-squares support vector machines and partial least squares in simultaneous spectrophotometric determination of cypermethrin, permethrin and tetramethrin
- Flow-Injection Solid Phase Partial Least-Squares Spectrophotometric Simultaneous Determination of Iron, Nickel and Zinc