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 gregorygundersen.com
Expectation of the Truncated Lognormal Distribution
| | sriku.org
Generating values that fit a probability distribution | Codaholic
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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.
| | sander.ai
Addendum: quantifying our flawed intuitions - Sander Dieleman
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| | This is an addendum to my post about typicality, where I try to quantify flawed intuitions about high-dimensional distributions.
| | nelari.us
Using inverse transform sampling to generate random numbers in a given distribution // My thought repository
1.2 parsecs away

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| | In inverse transform sampling, the inverse cumulative distribution function is used to generate random numbers in a given distribution. But why does this work? And how can you use it to generate random numbers in a given distribution by drawing random numbers from any arbitrary distribution?
| | gouthamanbalaraman.com
On the Convergence of Hull White Monte Carlo Simulations - G B
6.7 parsecs away

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