Show simple item record

dc.contributor.authorDokuchaev, Nikolai
dc.date.accessioned2018-04-30T02:39:39Z
dc.date.available2018-04-30T02:39:39Z
dc.date.created2018-04-16T07:41:30Z
dc.date.issued2018
dc.identifier.citationDokuchaev, N. 2018. On causal extrapolation of sequences with applications to forecasting. Applied Mathematics and Computation. 328: pp. 276-286.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/66221
dc.identifier.doi10.1016/j.amc.2018.01.038
dc.description.abstract

The paper suggests a method of extrapolation of notion of one-sided semi-infinite sequences representing traces of two-sided band-limited sequences; this features ensure uniqueness of this extrapolation and possibility to use this for forecasting. This lead to a forecasting method for more general sequences without this feature based on minimization of the mean square error between the observed path and a predicable sequence. These procedure involves calculation of this predictable path; the procedure can be interpreted as causal smoothing. The corresponding smoothed sequences allow unique extrapolations to future times that can be interpreted as optimal forecasts.

dc.publisherElsevier Inc.
dc.titleOn causal extrapolation of sequences with applications to forecasting
dc.typeJournal Article
dcterms.source.volumeTBA
dcterms.source.numberTBA
dcterms.source.startPage1
dcterms.source.endPage20
dcterms.source.issn0096-3003
dcterms.source.titleApplied Mathematics and Computation
curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Science (EECMS)
curtin.accessStatusFulltext not available


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record