University of Oulu

Holmström, L., and Pasanen, L. (2017) Statistical Scale Space Methods. International Statistical Review, 85: 1–30. doi: 10.1111/insr.12155

Statistical scale space methods

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Author: Holmström, Lasse1; Ruha (née Pasanen), Leena1
Organizations: 1Department of Mathematical Sciences, University of Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 2.3 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe201704066003
Language: English
Published: Wiley, 2017
Publish Date: 2017-07-22
Description:

Summary

The goal of statistical scale space analysis is to extract scale-dependent features from noisy data. The data could be for example an observed time series or digital image in which case features in either different temporal or spatial scales would be sought. Since the 1990s, a number of statistical approaches to scale space analysis have been developed, most of them using smoothing to capture scales in the data, but other interpretations of scale have also been proposed. We review the various statistical scale space methods proposed and mention some of their applications.

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Series: International statistical review
ISSN: 0306-7734
ISSN-E: 1751-5823
ISSN-L: 0306-7734
Volume: 85
Issue: 1
Pages: 1 - 30
DOI: 10.1111/insr.12155
OADOI: https://oadoi.org/10.1111/insr.12155
Type of Publication: A2 Review article in a scientific journal
Field of Science: 112 Statistics and probability
Subjects:
Funding: Academy of Finland. Grant Numbers: 250862, 276022
Academy of Finland Grant Number: 250862
276022
Detailed Information: 250862 (Academy of Finland Funding decision)
276022 (Academy of Finland Funding decision)
Copyright information: © 2016 The Authors. International Statistical Review © 2016 International Statistical Institute. Published in this repository with the kind permission of the publisher.