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Estimating Functions

  • M. B. Rajarshi
Chapter
Part of the SpringerBriefs in Statistics book series (BRIEFSSTATIST)

Abstract

In this chapter, we discuss methods of estimation of parameters which assume that the conditional expectation and conditional variance of an observable given the past observations have been specified. These constitute semi-parametric methods for stochastic models. We begin with Conditional Least Squares estimation. Then, we discuss estimating functions in some details. The basic set of estimating functions can be conditionally uncorrelated or correlated. Optimality results for both these cases have been established. Asymptotic distribution of the estimator obtained from estimating equations is stated. Finally, we deal with methods of construction of confidence intervals based on estimating functions.

Keywords

Estimate Function Score Function Asymptotic Normal Distribution Conditional Little Square Unbiased Estimate Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© The Author(s) 2013

Authors and Affiliations

  1. 1.Department of StatisticsUniversity of PunePuneIndia

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