Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Preliminary Identification of Branching-Heteroscedasticity for Tree-Indexed Autoregressive Processes

  • Hwang, S.Y. (Department of Statistics, Sookmyung Women's University) ;
  • Choi, M.S. (Department of Statistics, Sookmyung Women's University)
  • Received : 20110700
  • Accepted : 20110900
  • Published : 2011.11.30
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Abstract

A tree-indexed autoregressive(AR) process is a time series defined on a tree which is generated by a branching process and/or a deterministic splitting mechanism. This short article is concerned with conditional heteroscedastic structure of the tree-indexed AR models. It has been usual in the literature to analyze conditional mean structure (rather than conditional variance) of tree-indexed AR models. This article pursues to identify quadratic conditional heteroscedasticity inherent in various tree-indexed AR models in a unified way, and thus providing some perspectives to the future works in this area. The identical conditional variance of sisters sharing the same mother will be referred to as the branching heteroscedasticity(BH, for short). A quasilikelihood but preliminary estimation of the quadratic BH is discussed and relevant limit distributions are derived.

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References

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