Conditional moments and linear regression for stable random variables

DOI10.1016/0304-4149(91)90078-QzbMath0739.62016OpenAlexW2059426179MaRDI QIDQ1180183

Murad S. Taqqu, Gennady Samorodnitsky

Publication date: 27 June 1992

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4149(91)90078-q

zbMATH Keywords

conditional momentsautoregressive modelsmoving averagesstable random vectorsub-Gaussian vectorsharmonizable vectorssymmetric alpha-stable processes

Mathematics Subject Classification ID

Infinitely divisible distributions; stable distributions (60E07) Linear regression; mixed models (62J05) Characteristic functions; other transforms (60E10) Characterization and structure theory of statistical distributions (62E10)

Related Items (10)

Fractional absolute moments of heavy tailed distributions ⋮ How do conditional moments of stable vectors depend on the spectral measure? ⋮ Necessary conditions for the existence of conditional moments of stable random variables ⋮ On stochastic processes with linear conditional moments ⋮ On a characterization of processes by the independence of linear forms in a triangular system ⋮ Infinite variance stable moving averages with long memory ⋮ Multiple regression on stable vectors ⋮ A testable version of the Pareto-Stable CAPM ⋮ Asymptotic behavior of conditional laws and moments of \(\alpha\)-stable random vectors, with application to upcrossing intensities ⋮ Guaranteed parameter estimation in a first order autoregressive progress with infinite variance

Cites Work

• Characterizations of almost surely continuous p-stable random Fourier series and strongly stationary processes
• Extrema of skewed stable processes
• Nonlinear regression of stable random variables
• Linear sample spaces and stable processes
• On the linearity of regression
• Some Structure Theorems for the Symmetric Stable Laws
• A representation theorem for symmetric stable processes and stable measures on H
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