期刊
APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
卷 17, 期 3, 页码 277-291出版社
JOHN WILEY & SONS LTD
DOI: 10.1002/asmb.445
关键词
model characterization; probability generating function; GMM; least squares; Yule-Walker; Monte Carlo
The paper presents new characterizations of the integer-valued moving average model. For four model variants, we give moments and probability generating functions. Yule-Walker and conditional least-squares estimators are obtained and studied by Monte Carlo simulation. A new generalized method of moment estimator based on probability generating functions is presented and shown to be consistent and asymptotically normal. The small sample performance is in some instances better than those of alternative estimators. Copyright (C) 2001 John Wiley & Sons, Ltd.
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