Dependent Data Models

Dirk P. Kroese and Joshua Chan
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Dirk P. Kroese: The University of Queensland, School of Mathematics and Physics

Chapter Chapter 10 in Statistical Modeling and Computation, 2014, pp 287-322 from Springer

Abstract: 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.

Keywords: Maximum Likelihood Estimate; Moving Average; Gaussian Model; Multivariate Normal Distribution; Precision Matrix (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4614-8775-3_10

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DOI: 10.1007/978-1-4614-8775-3_10

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