empirical likelihood by art b owen pdf qttb

Click to download:

==> empirical likelihood by art b owen pdf <==

Empirical likelihood, as introduced by Art B. Owen, is a nonparametric method of statistical inference that utilizes empirical distributions to estimate probabilities without assuming a specific parametric model. It is grounded in the idea of maximizing a likelihood function based on observed data while maintaining certain constraints, typically derived from the sample moments. This approach allows for the construction of confidence regions and hypothesis testing, offering a flexible alternative to traditional methods such as maximum likelihood estimation, which often require strong assumptions about the underlying distribution. In Owen's work, empirical likelihood is shown to have desirable properties, such as being robust to model misspecification and providing valid inferences even with small sample sizes. The method involves constructing an empirical likelihood function that reflects the data's characteristics and using it to derive inference procedures, like confidence intervals for parameters or functions of parameters. Owen's contributions have expanded the applicability of empirical likelihood across various statistical fields, making it a valuable tool in both theoretical and applied statistics. By combining empirical data with likelihood principles, this approach enhances the ability to draw meaningful conclusions from real-world datasets without the need for restrictive assumptions.