1. Probability and Distributions. 2. Multivariate Distributions. 3. Some Special Distributions. 4. Some Elementary Statistical Inferences 5. Consistency and Limiting Distributio...
This chapter contains sections titled: Why Robust Regression? M-Estimators and W-Estimators for Regression Computation Example: The Stack Loss Data Bounded-Influence Regression ...
Variable selection is fundamental to high-dimensional statistical modeling, including nonparametric regression. Many approaches in use are stepwise selection procedures, which c...
Principal component analysis is a widely used technique that provides an optimal lower-dimensional approximation to multivariate or functional datasets. These approximations can...
Research studying robustness of maximum likelihood (ML) statistics in covariance structure analysis has concluded that test statistics and standard errors are biased under sever...
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