On causal extrapolation of sequences with applications to forecasting
Access Status
Fulltext not available
Authors
Dokuchaev, Nikolai
Date
2018Type
Journal Article
Metadata
Show full item recordCitation
Dokuchaev, N. 2018. On causal extrapolation of sequences with applications to forecasting. Applied Mathematics and Computation. 328: pp. 276-286.
Source Title
Applied Mathematics and Computation
ISSN
School
School of Electrical Engineering, Computing and Mathematical Science (EECMS)
Collection
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.
Related items
Showing items related by title, author, creator and subject.
-
Saptoro, Agus (2010)ANN technology exploded into the world of process modelling and control in the late 1980’s. The technology shows great promise and is seen as a technology that could provide models for most systems without the need to ...
-
Hussen, Chawarwan M. (2009)Given the importance of the reserves disclosures for investors and regulators, it is surprising to them that there has been a lot of focus, which is elaborated on in Chapter 2, on how the reserves data are prepared and ...
-
Dokuchaev, Nikolai (2013)We study causal dynamic smoothing of discrete time processes via approximation by band-limited discrete time processes. More precisely, a part of the historical path of the underlying process is approximated in Euclidean ...