Gott Method: A Bayesian-inference-based prediction of duration of ongoing events

Presented here is a short script for determing future longevity of an observable ongoing event.
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Mise à jour 14 mai 2015

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Written by Tyler L. Coye (2015)
This script will estimate the future longevity (tfuture) of various
observables.

Based on the paper "Implications of the Copernican Principle for Our
Future Prospects" by J. Richard Gott III (1993).

Input:
tpast = (tnow - tbegin) = length of time something has been observed in
the past.
tbegin = time of the first observation
tnow = present time

Outputs:
tfuture interval estimation (j < tfuture < h) with 95% confidence
tfuture interval estimation (a < tfuture < b) with 50% confidence

EXAMPLE:
This is an example using the gott script.
This example was taken from Gott(1993).

Our species is roughly 200,000 years old. We want to etimate the future
longevity of our species. So, we let tpast = 200,000. Using the gott
script we will estimate tfuture:

5128.2051 < tfuture < 7800000 (95% Confidence Level)
*The human race will have a future longeveity between 5128.2051 years and
7800000 years, with 95% confidence.

66666.6667 < tfuture < 600000 (50% Confidence Level)
*The human race will have a future longevity between 66666.6667 <
tfuture < 600000, with 50% Confidence.

Citation pour cette source

Tyler Coye (2024). Gott Method: A Bayesian-inference-based prediction of duration of ongoing events (https://www.mathworks.com/matlabcentral/fileexchange/50859-gott-method-a-bayesian-inference-based-prediction-of-duration-of-ongoing-events), MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2014b
Compatible avec toutes les versions
Plateformes compatibles
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Version Publié le Notes de version
1.0.0.0