Functions and Data for a Course on Modern Regression and Classification
Add horizontal lines to plot.
Between group SS for y, for all possible splits on values of x
Compare accuracy of alternative classification methods
Given actual and predicted group assignments, give the confusion matri...
Cross-validation estimate of predictive accuracy for clustered data
Cross-validation estimate of accuracy from GAM model fit
Tabulate vector of dates by specified time event
Functions and Data for a Course in Modern Regression
Random forest fit to residuals from GAM model
Calculate Error Rates for Linear Discriminant Model
Plot Protection Device Effectiveness Measure Against Year
Random forests estimate of predictive accuracy for clustered data
Calculate Error Rates for randomForest model
Calculate Error Rates for rpart model
Simulate (repeated) regression calculations
Extract ratio of ratios estimate of safety device effectiveness, from ...
Functions and data are provided that support a course that emphasizes statistical issues of inference and generalizability. The functions are designed to make it straightforward to illustrate the use of cross-validation, the training/test approach, simulation, and model-based estimates of accuracy. Methods considered are Generalized Additive Modeling, Linear and Quadratic Discriminant Analysis, Tree-based methods, and Random Forests.