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.
125 Downloads
Updated 14 May 2015

View License

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.

Cite As

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. Retrieved .

MATLAB Release Compatibility
Created with R2014b
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on Verification, Validation, and Test in Help Center and MATLAB Answers

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Published Release Notes
1.0.0.0