Efficient methods for estimating constrained parameters with applications to regularized (lasso) logistic regression

Keyphrases

• Lasso Regression 100%
• Constrained Parameters 100%
• Bound Algorithm 100%
• Newton's Method 50%
• EM Algorithm 16%
• Numerical Examples 16%
• Least Absolute Shrinkage and Selection Operator (LASSO) 16%
• Logistic Regression Model 16%
• Microarray Data 16%
• Convergence Rate 16%
• CPU Time 16%
• Colon 16%
• Fast Convergence 16%
• Number of Iterations 16%
• Penalty Function 16%
• Assure 16%
• Real Examples 16%
• Iteration Times 16%
• Cox Proportional Hazards Model 16%
• Multinomial Logistic 16%
• Alternative Algorithms 16%
• Monotonic Convergence 16%
• Bootstrap Variance Estimator 16%
• Kyphosis 16%
• Linear Inequality Constraints 16%
• Majorization Matrix 16%
• Down Syndrome 16%

Mathematics

• Newton's Method 100%
• Logistic Regression 100%
• Matrix (Mathematics) 33%
• Numerical Example 33%
• Variance Estimation 33%
• Majorization 33%
• Logistic Regression Model 33%
• Inequality Constraint 33%
• Cox Proportional Hazards Model 33%
• Linear Inequality 33%