Explore >> Select a destination
|
You are here 
|
www.jeremiecoullon.com | ||
| | | | |
www.randomservices.org
|
|
| | | | | [AI summary] The text covers various topics in probability and statistics, including continuous distributions, empirical density functions, and data analysis. It discusses the uniform distribution, rejection sampling, and the construction of continuous distributions without probability density functions. The text also includes data analysis exercises involving empirical density functions for body weight, body length, and gender-specific body weight. | |
| | | | |
dfm.io
|
|
| | | | | [AI summary] This document provides a comprehensive guide to estimating autocorrelation times in Markov Chain Monte Carlo (MCMC) simulations. It begins by explaining the importance of autocorrelation in MCMC and how it affects the effective sample size. The text then introduces several methods for estimating autocorrelation times, including the Goodman & Weare (2010) method and a newer algorithm developed by the author (DFM 2017). The document also discusses the limitations of these methods with short chains and introduces a maximum likelihood approach using the celerite library to fit an autocorrelation model. Finally, it concludes with recommendations for choosing appropriate chain lengths based on the estimated autocorrelation times. | |
| | | | |
artowen.su.domains
|
|
| | | | | Monte Carlo theory, methods and examples | |
| | | | |
web.navan.dev
|
|
| | | Tutorial on creating an image classifier model using TensorFlow which detects malaria | ||
