DENSITY-ESTIMATION IN STRONGLY DEPENDENT NONLINEAR TIME-SERIES
CHENG, B; ROBINSON, PM
刊名STATISTICA SINICA
1991-07-01
卷号1期号:2页码:335-359
关键词DENSITY ESTIMATION LONG MEMORY TIME SERIES NONLINEAR TIME SERIES NORMAL AND NONNORMAL LIMITING DISTRIBUTIONS INTEGRATED MEAN SQUARED ERROR
ISSN号1017-0405
英文摘要Smoothed nonparametric density estimates can be useful in analysing nonlinear time series. Their asymptotic properties in weakly dependent series, including limiting distributions and mean squared error, are known to be similar to those in independent series. Robinson (1987) found evidence that these properties may not hold in strongly dependent, or "long-memory" Gaussian time series. The present paper derives normal and non-normal limiting distributions in case of long-memory nonlinear series, provides a numerical comparison of integrated mean squared error, and reports estimates based on simulated series.
WOS研究方向Mathematics
语种英语
出版者STATISTICA SINICA
WOS记录号WOS:A1991GA76900002
内容类型期刊论文
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/27733]  
专题中国科学院数学与系统科学研究院
作者单位1.CHINESE ACAD SCI,INST APPL MATH,BEIJING,PEOPLES R CHINA
2.UNIV LONDON LONDON SCH ECON & POLIT SCI,DEPT CYTOL,LONDON WC2A 2AE,ENGLAND
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CHENG, B,ROBINSON, PM. DENSITY-ESTIMATION IN STRONGLY DEPENDENT NONLINEAR TIME-SERIES[J]. STATISTICA SINICA,1991,1(2):335-359.
APA CHENG, B,&ROBINSON, PM.(1991).DENSITY-ESTIMATION IN STRONGLY DEPENDENT NONLINEAR TIME-SERIES.STATISTICA SINICA,1(2),335-359.
MLA CHENG, B,et al."DENSITY-ESTIMATION IN STRONGLY DEPENDENT NONLINEAR TIME-SERIES".STATISTICA SINICA 1.2(1991):335-359.
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