2013
DOI: 10.3390/e15062246
|View full text |Cite
|
Sign up to set email alerts
|

Bootstrap Methods for the Empirical Study of Decision-Making and Information Flows in Social Systems

Abstract: We characterize the statistical bootstrap for the estimation of informationtheoretic quantities from data, with particular reference to its use in the study of large-scale social phenomena. Our methods allow one to preserve, approximately, the underlying axiomatic relationships of information theory-in particular, consistency under arbitrary coarse-graining-that motivate use of these quantities in the first place, while providing reliability comparable to the state of the art for Bayesian estimators. We show h… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
46
0

Year Published

2014
2014
2024
2024

Publication Types

Select...
8
1
1

Relationship

2
8

Authors

Journals

citations
Cited by 50 publications
(47 citation statements)
references
References 28 publications
0
46
0
Order By: Relevance
“…With the resulting topic model, we can then compute the semantic distance between all pairs of pages using the Jensen-Shannon distance (JSD), a measure that quantifies the distinguishability of two distributions [54]. This gives us a weighted semantic network that we can compare to the network of hyperlinks between pages.…”
Section: Semantic Coherencementioning
confidence: 99%
“…With the resulting topic model, we can then compute the semantic distance between all pairs of pages using the Jensen-Shannon distance (JSD), a measure that quantifies the distinguishability of two distributions [54]. This gives us a weighted semantic network that we can compare to the network of hyperlinks between pages.…”
Section: Semantic Coherencementioning
confidence: 99%
“…The estimate of bias comes from comparing the entropy of the empirical distribution to estimates of entropy from several bootstrap datasets drawn randomly according to the empirical distribution. See [10] for more details.…”
Section: Estimating Mutual Information From Datamentioning
confidence: 99%
“…Nonetheless, I estimate entropy with the computer program THOTH (DeDeo, Hawkins, Klingenstein, & Hitchcock, 2013) which uses a bootstrap technique that minimizes bias and also provides confidence intervals for the entropy estimate. years).…”
Section: Declaration Of Conflicting Interestsmentioning
confidence: 99%