Probability Distributome: A Web Computational Infrastructure for Exploring the Properties, Interrelations, and Applications of Probability Distributions.

TitleProbability Distributome: A Web Computational Infrastructure for Exploring the Properties, Interrelations, and Applications of Probability Distributions.
Publication TypeJournal Article
Year of Publication2016
AuthorsDinov, Ivo D., Siegrist Kyle, Pearl Dennis K., Kalinin Alexandr, and Christou Nicolas
JournalComput Stat
Volume31
Issue2
Pagination559-577
Date Published2016 Jun
ISSN0943-4062
Abstract

Probability distributions are useful for modeling, simulation, analysis, and inference on varieties of natural processes and physical phenomena. There are uncountably many probability distributions. However, a few dozen families of distributions are commonly defined and are frequently used in practice for problem solving, experimental applications, and theoretical studies. In this paper, we present a new computational and graphical infrastructure, the Distributome, which facilitates the discovery, exploration and application of diverse spectra of probability distributions. The extensible Distributome infrastructure provides interfaces for (human and machine) traversal, search, and navigation of all common probability distributions. It also enables distribution modeling, applications, investigation of inter-distribution relations, as well as their analytical representations and computational utilization. The entire Distributome framework is designed and implemented as an open-source, community-built, and Internet-accessible infrastructure. It is portable, extensible and compatible with HTML5 and Web2.0 standards (http://Distributome.org). We demonstrate two types of applications of the probability Distributome resources: computational research and science education. The Distributome tools may be employed to address five complementary computational modeling applications (simulation, data-analysis and inference, model-fitting, examination of the analytical, mathematical and computational properties of specific probability distributions, and exploration of the inter-distributional relations). Many high school and college science, technology, engineering and mathematics (STEM) courses may be enriched by the use of modern pedagogical approaches and technology-enhanced methods. The Distributome resources provide enhancements for blended STEM education by improving student motivation, augmenting the classical curriculum with interactive webapps, and overhauling the learning assessment protocols.

DOI10.1007/s00180-015-0594-6
Alternate JournalComput Stat
PubMed ID27158191
PubMed Central IDPMC4856044
Grant ListU54 EB020406 / EB / NIBIB NIH HHS / United States
P20 NR015331 / NR / NINR NIH HHS / United States
P30 DK089503 / DK / NIDDK NIH HHS / United States
U54 RR021813 / RR / NCRR NIH HHS / United States
P50 NS091856 / NS / NINDS NIH HHS / United States