Algorithms for generating surrogate data for sparsely quantized time series

DOI10.1016/J.PHYSD.2007.04.006zbMath1123.62067OpenAlexW1992979470MaRDI QIDQ2372314

Tomoya Suzuki, Masuo Suzuki, Tohru Ikeguchi

Publication date: 26 July 2007

Published in: Physica D (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physd.2007.04.006

zbMATH Keywords

econophysicsquantized datafalse rejectionthe method of surrogate data

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Time series analysis of dynamical systems (37M10)

Related Items (1)

Chaoticity versus stochasticity in financial markets: are daily S\&P 500 return dynamics chaotic?

Uses Software

• itsmr

Cites Work

• Unnamed Item
• Testing for nonlinearity in time series: the method of surrogate data
• Measuring the strangeness of strange attractors
• Surrogate time series.
• Determinism in Financial Time Series
• Introduction to Econophysics

This page was built for publication: Algorithms for generating surrogate data for sparsely quantized time series