A DATA-DRIVEN NONPARAMETRIC SPECIFICATION TEST FOR DYNAMIC REGRESSION MODELS

DOI10.1017/S0266466606060282zbMath1125.62041MaRDI QIDQ3408512

Alain Guay, Emmanuel Guerre

Publication date: 14 November 2006

Published in: Econometric Theory (Search for Journal in Brave)

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20)

Related Items (6)

SEQUENTIAL MONITORING OF CHANGES IN DYNAMIC LINEAR MODELS, APPLIED TO THE U.S. HOUSING MARKET ⋮ Robust adaptive rate-optimal testing for the white noise hypothesis ⋮ Data-driven smooth tests for the martingale difference hypothesis ⋮ A neural network method for nonlinear time series analysis ⋮ TESTS OF THE MARTINGALE DIFFERENCE HYPOTHESIS USING BOOSTING AND RBF NEURAL NETWORK APPROXIMATIONS ⋮ Goodness-of-fit tests for functional data

Cites Work

• Nonparametric bootstrap analysis with applications to demographic effects in demand functions
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• Comparing nonparametric versus parametric regression fits
• Asymptotic equivalence of nonparametric regression and white noise
• Adaptive hypothesis testing using wavelets
• Adaptive tests of linear hypotheses by model selection
• Generalized likelihood ratio statistics and Wilks phenomenon
• Data-driven testing the fit of linear models
• Data-driven rate-optimal specification testing in regression models
• Adaptive minimax testing in the discrete regression scheme
• Test of Significance Based on Wavelet Thresholding and Neyman's Truncation
• Goodness-of-Fit Tests for Parametric Regression Models
• A Parametric Approach to Flexible Nonlinear Inference
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• Hypothesis Testing in Semiparametric and Nonparametric Models for Econometric Time Series
• Consistent Specification Testing Via Nonparametric Series Regression
• Goodness-of-fit tests for kernel regression with an application to option implied volatilities

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