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Improving density estimators of discretely observed processes by interpolation
Örebro University, Swedish Business School at Örebro University.
2009 (English)In: Journal of Statistical Planning and Inference, ISSN 0378-3758, E-ISSN 1873-1171, Vol. 139, no 6, p. 1847-1855Article in journal (Refereed) Published
Abstract [en]

We consider density estimation for a smooth stationary process Xt, tR, based on a discrete sample Yi=XΔi, i=0,…,n=T/Δ. By a suitable interpolation scheme of order p, we augment data to form an approximation Xp,t, t[0,T], of the continuous-time process and base our density estimate on the augmented sample path. Our results show that this can improve the rate of convergence (measured in terms of n) of the density estimate. Among other things, this implies that recording n observations using a small Δ can be more efficient than recording n independent observations.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2009. Vol. 139, no 6, p. 1847-1855
National Category
Social Sciences Probability Theory and Statistics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:oru:diva-5752DOI: 10.1016/j.jspi.2008.06.017ISI: 000264711600003Scopus ID: 2-s2.0-60949083868OAI: oai:DiVA.org:oru-5752DiVA, id: diva2:174095
Available from: 2009-02-19 Created: 2009-02-19 Last updated: 2017-12-13Bibliographically approved

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Sköld, Martin

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