|
You are here |
erikbern.com | ||
| | | | |
blog.demofox.org
|
|
| | | | | There is ~400 lines of standalone C++ code that implements the main ideas in this post. You can find it at: https://github.com/Atrix256/MetropolisMCMC In previous posts I showed how to generate random numbers from a specific distributing by using two techniques: Rejection Sampling: https://blog.demofox.org/2017/08/08/generating-random-numbers-from-a-specific-distribution-with-rejection-sampling/ Inverting the CDF: https://blog.demofox.org/2017/08/05/generating-random-numbers-from-a-specific-distribution-by-inverting-the-cdf/ This post will show how to do it... | |
| | | | |
667-per-cm.net
|
|
| | | | | This post could also be subtitled "Residual deviance isn't the whole story." My favorite book on logistic regression is by Dr Joseph Hilbe, Logistic Regression Models, CRC Press, 2009, Chapman & Hill. It is a solidly frequentist text, but its discussion of models and rich examples make that besides the point. Except in one case.... | |
| | | | |
freerangestats.info
|
|
| | | | | The success rate (proportion of times the true value is covered by the interval) of 95% confidence intervals from the bootstrap when estimating population standard deviation can be very poor for complex mixed distributions, such as real world weekly income from a modest sample size (<20,000). | |
| | | | |
www.quantstart.com
|
|
| | | Bayesian Statistics: A Beginner's Guide | ||