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Density estimation for spatial linear processes
Hallin, M; Lu, ZD; Tran, LT
2001-08-01
Source PublicationBERNOULLI
ISSN1350-7265
Volume7Issue:4Pages:657-668
AbstractThe problem of estimating the marginal densities of a spatial linear process, observed over a grid of Z(N), is considered. Under general conditions, kernel density estimators computed at any k-tuple of sites are shown to be asymptotically multivariate normal. Their limiting covariance matrix is also computed. Despite the huge development of nonparametric estimation methods in the analysis of time series data, little has so far been done to introduce them into the context of random fields. The generalization is far from trivial since the points of Z(N) do not have a natural ordering when N>1. No mixing conditions are required, but linearity is assumed.
Keywordbandwidth density estimation kernel spatial process
Language英语
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:000170789300007
PublisherINT STATISTICAL INST
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/16253
Collection中国科学院数学与系统科学研究院
Corresponding AuthorHallin, M
Affiliation1.Free Univ Brussels, ISRO, B-1050 Brussels, Belgium
2.Chinese Acad Sci, Inst Syst Sci, Beijing 100080, Peoples R China
3.Indiana Univ, Dept Math, Bloomington, IN 47405 USA
Recommended Citation
GB/T 7714
Hallin, M,Lu, ZD,Tran, LT. Density estimation for spatial linear processes[J]. BERNOULLI,2001,7(4):657-668.
APA Hallin, M,Lu, ZD,&Tran, LT.(2001).Density estimation for spatial linear processes.BERNOULLI,7(4),657-668.
MLA Hallin, M,et al."Density estimation for spatial linear processes".BERNOULLI 7.4(2001):657-668.
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