Weighted denoised minimum distance estimation in a regression model with autocorrelated measurement errors

Mathematics

• Auxiliary Variable 100%
• Regression Model 100%
• Measurement Error 100%
• Least Square 50%
• Real Data 50%
• Linear Regression Model 50%
• Convergence Rate 50%
• Asymptotic Normality 50%
• Covariate 50%
• Regressors 50%
• Strong Convergence 50%
• Square Estimator 50%
• Error Variance 50%
• Regression Coefficient 50%
• Optimal Choice 50%
• Smaller Variance 50%
• Autocorrelation Coefficient 50%

Keyphrases

• Regression Model 100%
• Measurement Error 100%
• Minimum Distance Estimator 100%
• Auxiliary Variable 50%
• Finite Sample Performance 25%
• Undersmoothing 25%
• Linear Regression Model 25%
• Regression Coefficient 25%
• Autocorrelation 25%
• Previous Literature 25%
• Error Variance 25%
• Regressor 25%
• Large Sample Properties 25%
• Least Squares Estimator 25%
• Error Structure 25%
• Consistency Asymptotic Normality 25%
• Strong Convergence Rate 25%