BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Estimation, Inference Specification

Estimation, Inference Specification

Estimation, Inference Specification
Stock photo: cover may vary

Estimation, Inference Specification Paperback - 1996

by White

Add to wish list
  • Used
  • Paperback
New

Description

Paperback. LIKE NEW/LIKE NEW.
Ask the seller a question Add to wish list
A$46.73
A$141.66 Delivery to USA
Standard delivery: 20 to 30 days
More delivery options
Dropship order
Ships from Gigliotti (United Kingdom)

Details

  • Title Estimation, Inference Specification
  • Author White
  • Binding Paperback
  • Edition [ Edition: first
  • Condition New
  • Pages 396
  • Volumes 1
  • Language ENG
  • Publisher Cambridge University Press, West Nyack, New York, U.S.A.
  • Publication date 1996-06-28
  • Bookseller's Inventory # SKU10721
  • ISBN 9780521574464 / 0521574463
  • Weight 1.15 lbs (0.52 kg)
  • Dimensions 8.94 x 6 x 0.77 in (22.71 x 15.24 x 1.96 cm)
  • Category Business / Economics / Finance
  • Dewey Decimal Code 330.015
  • Quantity available 1

About Gigliotti United Kingdom

Biblio member since 2025

All books are carefully selected for quality and are as described on Biblio. We ship daily
We all want our customers to have the best shopping experience.We will extra charge additional international shipping insurance for orders shipped to the United Kingdom.

Terms of Sale:

30 day return guarantee, with full refund including original shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

We will extra charge additional international shipping insurance for orders shipped to the United Kingdom.

Browse books from Gigliotti

Reader reviews for Estimation, Inference Specification

From the publisher

This book examines the consequences of misspecifications ranging from the fundamental to the nonexistent for the interpretation of likelihood-based methods of statistical estimation and interference. Professor White first explores the underlying motivation for maximum-likelihood estimation, treats the interpretation of the maximum-likelihood estimator (MLE) for misspecified probability models and gives the conditions under which parameters of interest can be consistently estimated despite misspecification and the consequences of misspecification for hypothesis testing in estimating the asymptotic covariance matrix of the parameters. The analysis concludes with an examination of methods by which the possibility of misspecification can be empirically investigated and offers a variety of tests for misspecification.
tracking-