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Dependent Data Models

In: Statistical Modeling and Computation

Author

Listed:
  • Dirk P. Kroese

    (The University of Queensland, School of Mathematics and Physics)

  • Joshua C. C. Chan

    (Australian National University, Department of Economics)

Abstract

In the models considered so far the responses $$Y _{1},\ldots,Y _{n}$$ have been assumed to be independent given the model parameters. Though convenient, this independence assumption is implausible in two common situations. First, in the case of time series—observations measured over time—the responses typically exhibit strong serial dependence. For example, high unemployment tends to last for a long period of time; given a high unemployment rate this period, one would expect that the unemployment rates in the next few periods would also be high.

Suggested Citation

  • Dirk P. Kroese & Joshua C. C. Chan, 2014. "Dependent Data Models," Springer Books, in: Statistical Modeling and Computation, edition 127, chapter 0, pages 287-322, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4614-8775-3_10
    DOI: 10.1007/978-1-4614-8775-3_10
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