Course Description
This course introduces a wide variety of nonparametric techniques for performing statistical inference and prediction, emphasizing both conceptual foundations and practical implementation. Basictheoretical justification is also provided. The content covers three broad themes:
(i) rank-type and order-type methods for handling location, dispersion, correlation, distribution and regression problems,
(ii) resampling-type procedures for testing and assessing precision, and
(iii) smoothing-type techniques for estimation and prediction. Topics include Wilcoxon signed-rank test, Mann-Whitney rank sum test, Spearman’s rho, Kendall’s tau, Kruskal-Wallis test, Kolmogorov-Smirnov test, bootstrapping, Jackknife, subsampling, permutation tests, kernel method, k-nearest neighbour, tree-based method, classification, etc.
CUHK
STAT3005 Applied Nonparametric Statistics