A Broad Class of Partially Specified Autoregressions on Multi-Casting Data
  • Baek, J. S.
  • Choi, M. S.
  • Hwang, S. Y.
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초록

Extending the bifurcating autoregressive (BAR) process (cf. Cowan and Staudte, 1986) to multi-casting (multi-splitting) data, Hwang and Choi (2009) introduced multi-casting autoregression (MCAR, for short) defined on multi-casting tree structured data. This article is concerned with the case when the MCAR model is partially specified only through conditional mean and variance without directly imposing autoregressive (AR) structure. The resulting class of models will be referred to as P-MCAR (partially specified MCAR). The P-MCAR considerably enlarges the class of multi-casting models including (as special cases) MCAR, random coefficient MCAR, conditionally heteroscedastic multi-casting models and binomial-thinning processes. Moment structures for this broad P-MCAR class are investigated. Least squares (LS) estimation method is discussed and asymptotic relative efficiency (ARE) of the generalized-LS over ordinary-LS is obtained in a closed form. A simulation study is conducted to illustrate results.

키워드

Autoregressive (AR) processMulti-casting dataPartially specified modelPathwise stationarityCELL LINEAGEMODELS
제목
A Broad Class of Partially Specified Autoregressions on Multi-Casting Data
저자
Baek, J. S.Choi, M. S.Hwang, S. Y.
DOI
10.1080/03610926.2010.521282
발행일
2012-01
유형
Article
저널명
Communications in Statistics - Theory and Methods
41
1
페이지
178 ~ 193