In a post on LinkedIn, David Vose argues that the advantages of Latin Hypercube sampling (LHS) over Monte Carlo are so minimal that “LHS does not deserve a place in modern…
Lonnie Chrisman
Lonnie Chrisman is Lumina's Chief Technical Officer, where he heads engineering and development of Analytica. He has a PhD in Artificial Intelligence and Computer Science from Carnegie Mellon University and a Bachelor’s degree in Electrical Engineering from University of California at Berkeley.
Author Posts
Latin hypercube vs. Monte Carlo sampling
Does GPT-4 pass the Turing test?
UCSD researchers conducted an online Turing test of GPT-4 with 652 human participants. Humans were not fooled ~60% of the time.
AI weekly updates with Lonnie Chrisman
Get the latest AI insights with Lonnie Chrisman’s weekly updates. Follow us on social for trends and developments from an AI expert.
The effects of gas prices and electricity tariffs on heat pump economics
You might expect that a spike in natural gas prices from Russia’s war on Ukraine would lower carbon emissions—making electrification more economical. However, that is not the case.
Pi Day comparison: Monte Carlo vs Latin hypercube vs Sobol sampling
This blog will be visiting the dart-throwing method of estimating π and comparing how fast or slow different sampling techniques converge to the actual value of π. The sampling techniques…
The deadly pillow fallacy
On the surface it seems absurd that a pillow could cause all that death and disease. But, you should be careful not to let your preconceived beliefs taint your analysis of the data.
Voluntary vs. mandatory testing for naval crew selection
As COVID-19 testing becomes a routine part of doing business, some operations face the question of whether testing should be mandatory or voluntary.
Early COVID-19 decay rates for countries that have peaked
In previous articles [C20a, H20], my colleague and I have written about how the number of cases and deaths from COVID-19 follows a triangle shape over time when plotted with…