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 nelari.us
Using inverse transform sampling to generate random numbers in a given distribution // My thought repository
| | glowingpython.blogspot.com
The Glowing Python: Kernel Density Estimation with scipy
2.8 parsecs away

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| | This post continues the last one where we have seen how to how to fit two types of distribution functions (Normal and Rayleigh). This time ...
| | sriku.org
Generating values that fit a probability distribution | Codaholic
1.3 parsecs away

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| | [AI summary] The article explains how to generate random numbers that follow a specific probability distribution using a uniform random number generator, focusing on methods involving inverse transform sampling and handling both continuous and discrete cases.
| | austinrochford.com
Overthinking a Monte Carlo Estimate of | Austin Rochford
2.6 parsecs away

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| | While preparing the first in an upcoming series of posts on multi-armed bandits, I realized that a post diving deep on a simple Monte Carlo estimate of $\pi$ would be a useful companion, so here it is
| | gouthamanbalaraman.com
On the Convergence of Hull White Monte Carlo Simulations - G B
4.9 parsecs away

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| Discusses the convergence of the Monte-Carlo simulations of the Hull-White model