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Box-Muller Transform

Probability and Statistics

The Box-Muller transform is a method for generating pairs of independent, standard, normally distributed random numbers starting from a source of uniformly distributed random numbers. It is named after George Edward Pelham Box and Mervin Edgar Muller, who published the method, although the underlying idea was mentioned earlier by Raymond Paley and Norbert Wiener in their 1934 work on Fourier transforms. The transform was developed as a computationally efficient alternative to inverse transform sampling for producing Gaussian random values, though newer methods such as the ziggurat algorithm now outperform it on some hardware. This description is adapted from Wikipedia contributors under CC BY-SA 4.0; changes were made. https://creativecommons.org/licenses/by-sa/4.0/

Facts
Origin Year
1934 1
first mentioned explicitly by Paley and Wiener in their 1934 treatise on Fourier transforms
Classification
Object Kind
Operator 1
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Is Kind Of Object

Entity-backed identity for the object-kind enum value this mathematical object already carries, resolved to a mathematics concept by an explicit value-to-entity map (phase 3 bucket conversion, docs\design_entity_backed_browse_buckets_20260928.md). The object-kind fact itself stays on the object unchanged.

Sources
1. Box-Muller Transform (Wikipedia)
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