Inference for some time series models with random coefficients and infinite variance innovations

DOI10.1016/S0895-7177(00)00284-3zbMath0967.62071MaRDI QIDQ5936766

M. Shelton Peiris, A. Thavaneswaran

Publication date: 8 July 2001

Published in: Mathematical and Computer Modelling (Search for Journal in Brave)

zbMATH Keywords

time seriesdispersionrandom coefficientsstable distributionsautoregressiveheavy-tailsleast absolute deviation

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: estimation (62M09) Point estimation (62F10)

Related Items (3)

Random autoregressive models: A structured overview ⋮ Smoothed estimates for models with random coefficients and infinite variance innovations ⋮ Inference for some time series models with random coefficients and infinite variance innovations

Cites Work

• Unnamed Item
• Estimation in nonlinear time series models
• Prediction via estimating functions
• Parameter estimation for infinite variance fractional ARIMA
• Estimation for regression with infinite variance errors
• The foundations of finite sample estimation in stochastic processes
• ESTIMATION FOR NON-LINEAR TIME SERIES MODELS USING ESTIMATING EQUATIONS
• Autoregressive processes with infinite variance
• Minimum error dispersion linear filtering of scalar symmetric stable processes
• INFINITE VARIANCE STABLE ARMA PROCESSES
• TESTING FOR THE RANDOMNESS OF AUTOREGRESSIVE COEFFICIENTS
• A note on Model Reference Adaptive System (MRAS) estimate with infinite variance
• "Infinite Variance" and Research Strategy in Time Series Analysis
• Inference for some time series models with random coefficients and infinite variance innovations

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