Nonparametric Inference - STAT 824 - sp 2025

1:15 - 2:30 pm, Tuesday and Thursday, LeConte College 205

Course syllabus



Slides Annotated slides Code from class Topics eBook section
Lec_00_slides.pdf Course overview
Lec_01_slides.pdf Lec_01_slides_annotated.pdf R code CDF estimation
Lec_02_slides.pdf Lec_02_slides_annotated.pdf R code kernel density estimation
Lec_03_slides.pdf Lec_03_slides_annotated.pdf multivariate kernel density estimation
Lec_04_slides.pdf Lec_04_slides_annotated.pdf R code Nadaraya-Watson and local polynomial estimators
Lec_05_slides.pdf Lec_05_slides_annotated.pdf R code spline estimators
Lec_06_slides.pdf Lec_06_slides_annotated.pdf R code additive model for nonparametric multiple regression eBook
Lec_07_slides.pdf Lec_07_slides_annotated.pdf minimax theory eBook
Lec_08_slides.pdf Lec_08_slides_annotated.pdf R code bootstrap for the mean eBook
Lec_09_slides.pdf Lec_09_slides_annotated.pdf Edgeworth expansion and second-order correctness of the bootstrap eBook
Lec_10_slides.pdf Lec_10_slides_annotated.pdf bootstrap for statistical functionals, von Mises expansions eBook
Lec_11_slides.pdf Lec_11_slides_annotated.pdf bootstrap in regression eBook
Lec_12_slides.pdf Lec_12_slides_annotated.pdf Wilcoxon rank sum test eBook


LaTex/R Markdown templates: template.tex template.Rmd LaTex_symbols

Homework Topics Due Solutions
hw_01.pdf Hoeffding's inequality, KS test, Brownian bridge, kernel density estimation, Hölder smoothness, higher order kernels, CV for KDE bandwidth selection Tuesday, Feb 4th hw_01_sol.pdf
hw_02.pdf Multivariate KDE, far-between-ness of points in high-dimensional space, N-W and local polynomial estimators, CV for bandwidth selection Thursday, Feb 20th hw_02_sol.pdf
hw_03.pdf Cox-deBoor recursion, largest eigenvalue of a matrix, smoothing and penalized splines, Lindeberg CLT, least-squares splines Tuesday, Mar 4th hw_03_sol.pdf
hw_04.pdf Orthogonal series estimator, backfitting, sparse backfitting, bootstrap Tuesday, Apr 1st hw_04_sol.pdf
hw_05.pdf Influence functions, Edgeworth expansion, bootstrap, residual and wild bootstrap in regression Thursday, Apr 17th hw_05_sol.pdf


The project: Project description.pdf

Project componentTemplateDeadline
Choose topicBefore class Tues, Feb 4th.
Literature review lit_review_template.tex lit_review_template.bibWednesday, March 12th by midnight via Blackboard.
Proposal presentation (10 min)presentation_template.tex presentation_template.bibIn class on Thursday, March 27th.
Final presentation (20 min)Last two days of class, April the 22nd and 24th.
Written report written_report_template.tex written_report_template.bib Thursday, May 1st by midnight via Blackboard.


A few of the books I am using to prep for the course:

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