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DENSITY-ESTIMATION IN STRONGLY DEPENDENT NONLINEAR TIME-SERIES
CHENG, B; ROBINSON, PM
1991-07-01
Source PublicationSTATISTICA SINICA
ISSN1017-0405
Volume1Issue:2Pages:335-359
AbstractSmoothed 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.
KeywordDENSITY ESTIMATION LONG MEMORY TIME SERIES NONLINEAR TIME SERIES NORMAL AND NONNORMAL LIMITING DISTRIBUTIONS INTEGRATED MEAN SQUARED ERROR
Language英语
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:A1991GA76900002
PublisherSTATISTICA SINICA
Citation statistics
Cited Times:21[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/27734
Collection中国科学院数学与系统科学研究院
Affiliation1.CHINESE ACAD SCI,INST APPL MATH,BEIJING,PEOPLES R CHINA
2.UNIV LONDON LONDON SCH ECON & POLIT SCI,DEPT CYTOL,LONDON WC2A 2AE,ENGLAND
Recommended Citation
GB/T 7714
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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