Prediction theory for stationary functional time series
File(s)predfunc.pdf (269.98 KB)
Published version
Author(s)
Bingham, NH
Type
Journal Article
Abstract
We survey aspects of prediction theory in infinitely many dimensions, with a view to the theory and applications of functional time series.
Date Issued
2022-04-06
Date Acceptance
2022-04-01
Citation
Probability Surveys, 2022, 19, pp.160-184
ISSN
1549-5787
Publisher
Institute of Mathematical Statistics
Start Page
160
End Page
184
Journal / Book Title
Probability Surveys
Volume
19
Copyright Statement
© 2022 The Author(s). Published under the Creative Commons Attribution 4.0 International License.
License URL
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000784594100001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Physical Sciences
Statistics & Probability
Mathematics
Cramer representation
Kolmogorov isomorphism theorem
Verblunsky coefficients
Szego's theorem
Szego alternative
Beurling-Lax-Halmos theorem
functional time series
functional principal components
Karhunen-Loeve expansion
kernel methods
SZEGOS THEOREM
ORTHOGONAL POLYNOMIALS
BORODIN-OKOUNKOV
SPACE
CLASSIFICATION
DECOMPOSITION
DETERMINANT
RECURRENCE
WOLD
Publication Status
Published
Date Publish Online
2022-04-06