Shah R.D. Modern Statistical Methods

University of Cambridge, 2017. — 67 p.Introduction
Classical statistics
Kernel machines
Ridge regression
v-fold cross-validation
The kernel trick
Making predictions
Other kernel machines
Large-scale kernel machines
The Lasso and beyond
The Lasso estimator
Basic concentration inequalities
Convex analysis and optimization theory
Properties of Lasso solutions
Variable selection
Computation of Lasso solutions
Extensions of the Lasso
Graphical modelling
Conditional independence graphs
Structural equation modelling
The PC algorithm
High-dimensional inference
Multiple testing
Inference in high-dimensional regression
Index