Elements of Point Estimation Theory

Ron C. Mittelhammer
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Ron C. Mittelhammer: Washington State University, Program in Statistics and Department of Agricultural Economics

Chapter 7 in Mathematical Statistics for Economics and Business, 1996, pp 363-426 from Springer

Abstract: Abstract The problem of point estimation examined in this chapter is concerned with the estimation of the values of unknown parameters, or functions of parameters, that represent characteristics of interest relating to the probability space of some collection of economic, sociological, biological, or physical experiments. The outcomes generated by the collection of experiments are assumed to be outcomes of a random sample with some joint probability density function f(x 1 ,...,x n ; Θ). The random sample need not be from a population distribution, that is, it is not necessarily the case that X 1 ,..., X n are iid. The objective of point estimation will be to utilize functions of the random sample outcome to generate good (in some sense) estimates of the unknown characteristics of interest

Keywords: Mean Square Error; Unbiased Estimator; Best Linear Unbiased Estimator; Joint Density Function; Asymptotic Relative Efficiency (search for similar items in EconPapers)
Date: 1996
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DOI: 10.1007/978-1-4612-3988-8_7

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