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Model-Based Estimators

  • Diane Griffin Saphire
Part of the Lecture Notes in Statistics book series (LNS, volume 23)

Abstract

In this chapter we consider several superpopulation models of victimization and derive an estimate of θ on the basis of each. The fit of each model is tested using a X2 goodness of fit statistic for each of the years 1973 though 1975. We find that a correlated Bernoulli model is an inappropriate model of crime, while a homogeneous Bernoulli model and a Markov model provide better fits to the data. None of these models fits the data as well as the model under which the modified ad hoc estimator is consistent.

Keywords

Markov Model Estimate Standard Deviation Likelihood Inference Superpopulation Model Independent Bernoulli Random Variable 
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

© Springer-Verlag Berlin Heidelberg 1984

Authors and Affiliations

  • Diane Griffin Saphire
    • 1
  1. 1.Department of MathematicsTrinity UniversitySan AntonioUSA

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