Quasi-least-squares estimation in semimartingale regression models

DOI10.1080/17442508608833376zbMath0586.62137OpenAlexW2016999578WikidataQ126242203 ScholiaQ126242203MaRDI QIDQ3711555

Norbert Christopeit

Publication date: 1986

Published in: Stochastics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/17442508608833376

zbMATH Keywords

strong consistencysemimartingalelocal martingalestability propertiestransformation formulalinear regression modelsminimal eigenvaluestochastic regressorsmaximal eigenvalue of the design matrixquasi-least-squares estimation

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: estimation (62M09) Markov processes: estimation; hidden Markov models (62M05) Martingales with continuous parameter (60G44)

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General lemmas for stability analysis of linear continuous-time systems with slowly time-varying parameters ⋮ Laws of large numbers for semimartingales with applications to stochastic regression ⋮ Weighted least squares estimates in linear regression models for processes with uncorrelated increments ⋮ Adaptive stabilization for continuous time systems with disturbances ⋮ Parameter estimation in optional semimartingale regression models ⋮ ESTIMATING STRUCTURAL PARAMETERS IN REGRESSION MODELS WITH ADAPTIVE LEARNING ⋮ About the asymptotic behaviour of multidimensional Gaussian martingales and estimates in normal linear regression ⋮ Recursive approximate maximum likelihood estimation for a class of counting process models ⋮ Continuous time stochastic adaptive control: Non-explosion, \(\epsilon\)- consistency and stability ⋮ Optimal estimation for semimartingale neuronal models ⋮ Dynamic modelling and causality ⋮ Consistency property of extended least-squares parameter estimation for stochastic diffusion equation ⋮ On sequential estimation of parameters in semimartingale regression models with continuous time parameter.

Cites Work

• Semimartingales: A course on stochastic processes
• Asymptotic properties of general autoregressive models and strong consistency of least-squares estimates of their parameters
• A Functional Central Limit Theorem for Semimartingales
• Convergence of stochastic processes
• Least squares estimates in stochastic regression models with applications to identification and control of dynamic systems
• Unnamed Item

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