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Preliminary Identification of Branching-Heteroscedasticity for Tree-Indexed Autoregressive Processes
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 Title & Authors
Preliminary Identification of Branching-Heteroscedasticity for Tree-Indexed Autoregressive Processes
Hwang, S.Y.; Choi, M.S.;
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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.
 Keywords
Branching heteroscedasticity;quasilikelihood;tree-indexed AR;
 Language
English
 Cited by
1.
Contemporary review on the bifurcating autoregressive models : Overview and perspectives,;

Journal of the Korean Data and Information Science Society, 2014. vol.25. 5, pp.1137-1149 crossref(new window)
1.
Contemporary review on the bifurcating autoregressive models : Overview and perspectives, Journal of the Korean Data and Information Science Society, 2014, 25, 5, 1137  crossref(new windwow)
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