MyJournals Home  

RSS FeedsEntropy, Vol. 21, Pages 1120: Universal Sample Size Invariant Measures for Uncertainty Quantification in Density Estimation (Entropy)

 
 

15 november 2019 18:00:06

 
Entropy, Vol. 21, Pages 1120: Universal Sample Size Invariant Measures for Uncertainty Quantification in Density Estimation (Entropy)
 


Previously, we developed a high throughput non-parametric maximum entropy method (PLOS ONE, 13(5): e0196937, 2018) that employs a log-likelihood scoring function to characterize uncertainty in trial probability density estimates through a scaled quantile residual (SQR). The SQR for the true probability density has universal sample size invariant properties equivalent to sampled uniform random data (SURD). Alternative scoring functions are considered that include the Anderson-Darling test. Scoring function effectiveness is evaluated using receiver operator characteristics to quantify efficacy in discriminating SURD from decoy-SURD, and by comparing overall performance characteristics during density estimation across a diverse test set of known probability distributions.


 
226 viewsCategory: Informatics, Physics
 
Entropy, Vol. 21, Pages 1121: Distribution Structure Learning Loss (DSLL) Based on Deep Metric Learning for Image Retrieval (Entropy)
Entropy, Vol. 21, Pages 1119: Uncovering the Dependence of Cascading Failures on Network Topology by Constructing Null Models (Entropy)
 
 
blog comments powered by Disqus


MyJournals.org
The latest issues of all your favorite science journals on one page

Username:
Password:

Register | Retrieve

Search:

Physics


Copyright © 2008 - 2024 Indigonet Services B.V.. Contact: Tim Hulsen. Read here our privacy notice.
Other websites of Indigonet Services B.V.: Nieuws Vacatures News Tweets Nachrichten