Time series analysis with a skewed kalman filter

Philippe Naveau; Marc G. Genton; Caspar Ammann

Time series analysis with a skewed kalman filter

Philippe Naveau, Marc G. Genton, Caspar Ammann

Statistics

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

2 Scopus citations

Abstract

The analysis of time series has always played a central role in statistics. In this chapter, we focus on temporal state-space models for time series that can be decomposed in a sum of three components: a smooth trend, a skewness part, and noise. The first one is supposed to be deterministic and the other two random. Such time series decompositions are common in paleoclimate studies. The central element of the estimation procedure is the Kalman filter that has to be modified to deal with skewness.

Original language	English (US)
Title of host publication	Skew-Elliptical Distributions and Their Applications
Subtitle of host publication	A Journey Beyond Normality
Publisher	CRC Press
Pages	259-278
Number of pages	20
ISBN (Electronic)	9780203492000
ISBN (Print)	9781584884316
State	Published - Jan 1 2004

ASJC Scopus subject areas

General Mathematics

Cite this

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AB - The analysis of time series has always played a central role in statistics. In this chapter, we focus on temporal state-space models for time series that can be decomposed in a sum of three components: a smooth trend, a skewness part, and noise. The first one is supposed to be deterministic and the other two random. Such time series decompositions are common in paleoclimate studies. The central element of the estimation procedure is the Kalman filter that has to be modified to deal with skewness.

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ER -

Time series analysis with a skewed kalman filter

Abstract

ASJC Scopus subject areas

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