Sale!

George G. Judge – An Information Theoretic Approach to Econometrics

$64.00 $9.97

George G. Judge – An Information Theoretic Approach to Econometrics

Original Sales Price: $64

You Just Pay : $9.97

If you having any question, please contact us:
amazon4trader@gmail.com OR Skype: amazon4trader@gmail.com

Description

George G. Judge – An Information Theoretic Approach to Econometrics

Checkout more: Econometrics

This product is available

You can refer to the screenshots here :

Please contact us to get free sample

Description

This book is intended to provide the reader with a firm conceptual and empirical understanding of basic information-theoretic econometric models and methods. Because most data are observational, practitioners work with indirect noisy observations and ill-posed econometric models in the form of stochastic inverse problems.

Consequently, traditional econometric methods in many cases are not applicable for answering many of the quantitative questions that analysts wish to ask. After initial chapters deal with parametric and semiparametric linear probability models, the focus turns to solving nonparametric stochastic inverse problems.

In succeeding chapters, a family of power divergence measure-likelihood functions are introduced for a range of traditional and nontraditional econometric-model problems.

Finally, within either an empirical maximum likelihood or loss context, Ron C. Mittelhammer and George G. Judge suggest a basis for choosing a member of the divergence family


George G. Judge, An Information Theoretic Approach to Econometrics, Download An Information Theoretic Approach to Econometrics, Free An Information Theoretic Approach to Econometrics, An Information Theoretic Approach to Econometrics Torrent, An Information Theoretic Approach to Econometrics Review, An Information Theoretic Approach to Econometrics Groupbuy.

Reviews

There are no reviews yet.

Be the first to review “George G. Judge – An Information Theoretic Approach to Econometrics”