Nonparametric Statistics
Preface
Course overview
Scripts
1 Introduction
2 Kernel density estimation I
3 Kernel density estimation II
4 Kernel regression estimation I
5 Kernel regression estimation II
6 Nonparametric tests
Appendix
A Confidence intervals for the density function
B Review on parametric regression
- B.1 Linear regression
  - B.1.1 Model formulation and least squares
  - B.1.2 Model assumptions
- B.2 Logistic regression
  - B.2.1 Model formulation
  - B.2.2 Model assumptions and estimation
C Informal review on hypothesis testing
References
ISBN 978-84-09-29537-1
Licensed under
Published with bookdown

Notes for Nonparametric Statistics

Chapter 1 Introduction

We begin by reviewing some elementary results that will be employed during the course and which will also serve to introduce notation.