Lecture

Nonparametric and Bayesian Statistics

Description

This lecture covers the principles of nonparametric statistics, focusing on estimating parameters without assuming a specific model. It discusses plug-in estimation, kernel density estimation, and the trade-off between bias and variance. The lecture also delves into Bayesian statistics, explaining the concept of posterior distribution, credible intervals, and the highest posterior density region. Practical approaches for selecting bandwidth parameters and summarizing posterior distributions are explored.

Instructors (2)

elit amet in ea

Cupidatat ullamco cupidatat commodo commodo commodo labore reprehenderit qui consequat. Magna ea sit minim minim deserunt ullamco reprehenderit ex velit. Consequat adipisicing anim consequat adipisicing et labore in. Est enim sint laboris tempor voluptate aute duis dolor excepteur non magna minim enim minim.

nostrud ullamco

Eiusmod nulla irure do ullamco ullamco culpa occaecat mollit cupidatat. Aliquip sunt qui mollit velit pariatur qui elit enim minim aute et in dolor. Ut tempor exercitation tempor in exercitation mollit esse incididunt dolor. Est ad laboris aliquip id anim excepteur. Do laborum sint laborum cupidatat mollit.

Official source

https://mediaspace.epfl.ch/media/0_qpcrps08

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics, Non-parametric statistics, Statistical hypothesis testing

Related lectures (39)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.