Strong consistency in nonlinear stochastic regression models.

DOI10.1214/aos/1015952002zbMath1105.62355OpenAlexW1608214884MaRDI QIDQ1848804

Kostas Skouras

Publication date: 14 November 2002

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aos/1015952002

zbMATH Keywords

martingaleleast squares estimatorConsistencystochastic regression

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) General nonlinear regression (62J02)

Related Items (15)

Conditional least squares estimation in nonstationary nonlinear stochastic regression models ⋮ Dynamic Pricing and Learning with Finite Inventories ⋮ Estimation of the offspring mean in a supercritical or near-critical size-dependent branching process ⋮ Parameter estimation for stochastic Lotka-Volterra model driven by small Lévy noises from discrete observations ⋮ Asymptotics of the signed-rank estimator under dependent observations ⋮ Uniform moment bounds of Fisher's information with applications to time series ⋮ Robust nonlinear regression estimation in null recurrent time series ⋮ Non-asymptotic sequential confidence regions with fixed sizes for the multivariate nonlinear parameters of regression ⋮ Estimation of the offspring mean of a supercritical or near-critical size-dependent branching process ⋮ Nonlinear least-squares estimation ⋮ Nonasymptotic confidence sets of prescribed dimensions for parameters of nonlinear regressions ⋮ Regression analysis of stochastic fatigue crack growth model in a martingale difference framework ⋮ Nonlinear regressions with nonstationary time series ⋮ Estimation of harmonic component in regression with cyclically dependent errors ⋮ LEAST SQUARES ESTIMATION FOR NONLINEAR REGRESSION MODELS WITH HETEROSCEDASTICITY

Cites Work

• Strong consistency of least squares estimators in linear regression models
• Asymptotic theory of nonlinear least squares estimation
• Strong consistency of least squares estimates in dynamic models
• Strong consistency of Bayes estimates in nonlinear stochastic regression models
• Asymptotic properties of nonlinear least squares estimates in stochastic regression models
• Strong consistency of Bayes estimates in stochastic regression models
• Nonlinear Regression with Dependent Observations
• Consistency in Nonlinear Econometric Models: A Generic Uniform Law of Large Numbers
• Strong consistency in stochastic regression models via posterior covariance matrices
• Least squares estimates in stochastic regression models with applications to identification and control of dynamic systems

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