Optimal subsampling algorithms for composite quantile regression in massive data

Keyphrases

• Massive Data 100%
• Composite Quantile Regression 100%
• Optimal Subsampling 100%
• Quantile Regression 60%
• Subsampling Methods 40%
• Massive Datasets 40%
• Big Data 20%
• Regression Problem 20%
• Optimality Criteria 20%
• Loss Function 20%
• Ordinary Least Squares Regression 20%
• Asymptotic Properties 20%
• Practical Performance 20%
• Subsampling Probabilities 20%
• Two-step Method 20%
• Variance-covariance Matrix 20%
• Computational Limit 20%

Mathematics

• Quantile Regression 100%
• Probability Theory 28%
• Linear Models 14%
• Real Data 14%
• Simulated Data 14%
• Loss Function 14%
• Subsample 14%
• Numerical Analysis 14%
• Square Regression 14%
• Asymptotic Property 14%
• Two-Step Method 14%
• Variance Covariance Matrix 14%
• Optimality Criterion 14%
• Least Squares Method 14%
• Big Data 14%