Likelihood-Based Methods

Authored by: Dale L. Zimmerman

Handbook of Spatial Statistics

Print publication date:  March  2010
Online publication date:  March  2010

Print ISBN: 9781420072877
eBook ISBN: 9781420072884
Adobe ISBN:

10.1201/9781420072884-c4

 Download Chapter

 

Abstract

The previous chapter considered estimation of the parameters of a geostatistical model by a combination of method-of-moments and least squares methods. Those methods, collectively known as “classical geostatistics,” are relatively simple and do not explicitly require any distributional assumptions, but they are not optimal in any known sense. In this chapter, we present the estimation of parametric geostatistical models by likelihood-based approaches, which adhere to the likelihood principle (of course!) and, under appropriate regularity conditions, may be expected to have certain optimality properties.

 Cite
Search for more...
Back to top

Use of cookies on this website

We are using cookies to provide statistics that help us give you the best experience of our site. You can find out more in our Privacy Policy. By continuing to use the site you are agreeing to our use of cookies.