Pseudorandom number generation for engineering estimates

Version 1.1 (4,58 KB) von Sky Sartorius
Tools for generating pseudorandom numbers, primarily geared toward making engineering estimates.
176 Downloads
Aktualisiert 16 Mai 2021

A tool for random number generation on a distribution, such as a triangular distribution or PERT distribution, is very convenient for making estimates for physical values in the real world. Scientists and engineers often make estimates or assumptions, but they are also able to bracket the estimate based on experience or physics. For example, in estimating the mass of a small object, a normal distribution centered at my best guess could result in negative mass, which is known to be impossible. A triangular distribution allows quick and simple characterization of values as "probably M, but definitely not less than A or more than B."

The formulations here have some features that make it easy to integrate this capturing of uncertainty into scripts.

Example: Based purely on guesstimates that include a best guess and intuitive upper/lower limits, how much do a dime, nickel, and quarter weigh together?

% First, create a function based on randt to conveniently define and generate "uncertain variables."
uvar = @(x) randt(x,[1e5,1]);

dime = uvar([1 1.5 3.5]); %Pretty light, but not less than a gram..."
nickel = uvar([3 5 6]);
quarter = uvar([5 8 10]);

total = dime + nickel + quarter;

histogram(total,'Normalization','pdf');

Zitieren als

Sky Sartorius (2024). Pseudorandom number generation for engineering estimates (https://github.com/sky-s/randx), GitHub. Abgerufen .

Kompatibilität der MATLAB-Version
Erstellt mit R2016a
Kompatibel mit allen Versionen
Plattform-Kompatibilität
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Versionen, die den GitHub-Standardzweig verwenden, können nicht heruntergeladen werden

Version Veröffentlicht Versionshinweise
1.1

Added PERT distribution. Moved to GitHub repo.

1.0.0.0

Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das GitHub Repository.
Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das GitHub Repository.