Lecture

Estimating R: Maximum Likelihood Method

Description

This lecture covers the concept of estimating parameters in statistical models using the maximum likelihood method. It explains the process of choosing estimators and the properties desired in an estimator. The lecture also introduces the method of moments and the concept of point estimation, providing examples to illustrate the theoretical concepts.

Instructors (2)

occaecat cillum

Ullamco sint officia fugiat nulla proident Lorem et. Sit irure excepteur occaecat commodo magna elit nostrud ex nostrud est consequat. Veniam deserunt proident laboris eiusmod exercitation consequat nulla laborum consequat sit ad anim esse. Reprehenderit sunt ex qui cillum non nostrud incididunt exercitation voluptate cillum magna occaecat pariatur enim. Reprehenderit et adipisicing eu ea dolor nulla labore minim eiusmod incididunt. Non pariatur aliqua ad deserunt et voluptate proident tempor ex sunt minim non eiusmod.

exercitation nisi duis cillum

Voluptate fugiat officia magna enim ea consequat adipisicing cupidatat proident voluptate aliquip labore. Ut non nostrud sunt occaecat nisi mollit Lorem reprehenderit officia. Nostrud in duis adipisicing in proident anim consequat. Labore voluptate velit Lorem aute deserunt minim do voluptate incididunt pariatur ullamco ut. Labore Lorem ullamco labore ad do excepteur anim elit magna esse. Duis sunt reprehenderit officia nisi exercitation.

Official source

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

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

Related lectures (36)

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.