Asymptotic Normality of Moment Estimators for Multiple Time Series Count Data with an Application to Nonhomogeneous Poisson Process   :   Research Article 

作成者 大森, 裕浩
作成者 (ヨミ) オオモリ, ヤスヒロ
作成者の別表記 OMORI, Yasuhiro
日本十進分類法 (NDC) 331.19, 417
内容 A generalized model for multiple time series count data with serially correlated random effects is introduced to establish robust inference procedures. Observations are taken at possibly unequally spaced time intervals and random effects are assumed to have a stationary ergodic continuous time AR (1) process. This is a generalization of Zeger (1988) where observations are taken at equally spaced time intervals and random effects are assumed to follow a discrete autoregressive process. For reasons of robustness, the distributional forms of random effects is not specified. The central limit theorem is established to prove asymptotic normality of moment estimators.
公開者 千葉大学経済学会
コンテンツの種類 紀要論文 Departmental Bulletin Paper
DCMI資源タイプ text
ファイル形式 application/pdf
ISSN 0912-7216
NCID AN10005358
掲載誌情報 千葉大学経済研究 Vol.8 no.2/3 page.101-134 (19931208)
情報源 Economic journal of Chiba University
言語 英語
著者版フラグ publisher

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