NONPARAMETRIC SIGNIFICANCE TESTING IN MEASUREMENT ERROR MODELS
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Publication:5081788
DOI10.1017/S0266466621000220zbMath1493.62601OpenAlexW3168648694MaRDI QIDQ5081788
Publication date: 17 June 2022
Published in: Econometric Theory (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1017/s0266466621000220
Applications of statistics to economics (62P20) Nonparametric hypothesis testing (62G10) Asymptotic distribution theory in statistics (62E20)
Cites Work
- Consistent model specification tests
- Empirical and multiplier bootstraps for suprema of empirical processes of increasing complexity, and related Gaussian couplings
- An updated review of goodness-of-fit tests for regression models
- Gaussian approximation of suprema of empirical processes
- Variable selection in measurement error models
- New \(M\)-estimators in semi-parametric regression with errors in variables
- Deconvolution problems in nonparametric statistics
- Semiparametric estimation of censored selection models with a nonparametric selection mechanism
- Nonparametric estimation of the measurement error model using multiple indicators.
- Consistent hypothesis testing in semiparametric and nonparametric models for econometric time series
- Nonparametric regression with errors in variables
- Comparing nonparametric versus parametric regression fits
- Nonparametric model checks for regression
- Uniform confidence bands in deconvolution with unknown error distribution
- Significance testing in nonparametric regression based on the bootstrap.
- Bootstrap bandwidth selection in kernel density estimation from a contaminated sample
- Weak convergence and empirical processes. With applications to statistics
- Uniform confidence bands for nonparametric errors-in-variables regression
- Inference on distribution functions under measurement error
- Comparison and anti-concentration bounds for maxima of Gaussian random vectors
- On deconvolution with repeated measurements
- A ridge-parameter approach to deconvolution
- Testing the suitability of polynomial models in errors-in-variables problems
- On characterizing the gamma and the normal distribution
- CONSISTENT MODEL SPECIFICATION TESTS
- CONSISTENT SPECIFICATION TESTING WITH NUISANCE PARAMETERS PRESENT ONLY UNDER THE ALTERNATIVE
- Mathematical Foundations of Infinite-Dimensional Statistical Models
- Deconvolving kernel density estimators
- A NONPARAMETRIC HELLINGER METRIC TEST FOR CONDITIONAL INDEPENDENCE
- Nonparametric Regression Estimation in the Heteroscedastic Errors-in-Variables Problem
- Optimal Rates of Convergence for Deconvolving a Density
- A Consistent Conditional Moment Test of Functional Form
- Asymptotic Theory of Integrated Conditional Moment Tests
- NONPARAMETRIC SIGNIFICANCE TESTING
- Average derivative estimation with errors-in-variables
- Hypothesis Testing in Semiparametric and Nonparametric Models for Econometric Time Series
- Semiparametric Estimation of Index Coefficients
- Real Analysis and Probability
- A Semi‐parametric Regression Model with Errors in Variables
- Nonparametric regression with infinite order flat-top kernels
- SPECIFICATION TESTING FOR ERRORS-IN-VARIABLES MODELS
- AVERAGE DERIVATIVE ESTIMATION UNDER MEASUREMENT ERROR
- ON THE UNIFORM CONVERGENCE OF DECONVOLUTION ESTIMATORS FROM REPEATED MEASUREMENTS
- Semiparametric estimators of functional measurement error models with unknown error
- Non-Parametric Confidence Bands in Deconvolution Density Estimation
- Confidence Bands in Non-Parametric Errors-In-Variables Regression
- Asymptotic Normality of Kernel-Type Deconvolution Estimators
- Estimation of Nonlinear Models with Measurement Error
- Methodology for Non-Parametric Deconvolution When the Error Distribution is Unknown