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statisticaloddsandends.wordpress.com | ||
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statsandr.com
Learn how to use a Shiny app to compute probabilities for different probability distributions, used as a guide to read the most common statistical tables |
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gregorygundersen.com
[AI summary] The blog post derives the expected value of a left-truncated lognormal distribution, explaining the mathematical derivation and validating it with Monte Carlo simulations. |
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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. |
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dm13450.github.io
In my previous blog post I outlined the basic AR(1) model and the necessary maths needed to infer the unknown parameter \(\phi\). In this post I will outline some basic Julia code to build a MCMC sampler for such a model to infer the unknown parameter \(\phi\). |
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