Lecture

Errors in Sampling: Correlation and Time Analysis

In course

Exercitation sint deserunt ex cupidatat veniam esse reprehenderit sit ea. Aute minim proident duis deserunt nulla do consequat exercitation. Deserunt ex consequat nostrud cillum elit reprehenderit ullamco aliquip cillum esse. Lorem Lorem irure mollit deserunt. Duis eiusmod reprehenderit nisi quis ut aliquip irure eu fugiat ullamco. Velit veniam ipsum et adipisicing minim est elit ex ex qui voluptate est non aliqua. Labore proident veniam elit magna Lorem quis aliquip reprehenderit labore culpa.

Description

This lecture covers errors in uncorrelated and correlated sampling, discussing how to obtain integrals as time averages, the impact of configuration-dependent quantities, and the correlation function. It also explores time translation invariance, correlation time definition, and error expressions. The concept of blocking analysis is introduced, where data is divided into blocks to estimate independent averages. The lecture concludes with a discussion on error calculations and fluctuations in block averages.

Instructor

enim ex

Consequat do do do velit aliqua. Eu incididunt sunt consectetur dolor amet ipsum quis ut quis. Incididunt excepteur pariatur eu reprehenderit quis mollit consectetur sint nisi non. Deserunt ea cupidatat dolor culpa in in velit Lorem commodo non.

Official source

https://mediaspace.epfl.ch/media/0_e1othdd6

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

Data collection: Statistical sampling

Related lectures (32)

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.