Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Probability Distributions01:32

Probability Distributions

7.3K
 The probability of a random variable x  is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson...
7.3K
Probability Histograms01:17

Probability Histograms

11.8K
A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
11.8K
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

2.6K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
2.6K
Poisson Probability Distribution01:09

Poisson Probability Distribution

8.3K
A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
The...
8.3K
Binomial Probability Distribution01:15

Binomial Probability Distribution

11.2K
A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
11.2K
Probability Laws01:49

Probability Laws

41.1K
Overview
41.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

On nonlinear amplification: improved quantum limits for photon counting.

Optics express·2019
Same author

Permutationally invariant part of a density matrix and nonseparability of N-qubit states.

Physical review letters·2014
Same author

Measuring Trρn on single copies of ρ using random measurements.

Physical review letters·2012
Same author

Detecting the drift of quantum sources: not the de Finetti theorem.

Physical review letters·2011
Same author

Entanglement verification with finite data.

Physical review letters·2011
Same author

Entanglement of spin waves among four quantum memories.

Nature·2010
Same journal

Erratum: Low-dimensional model for adaptive networks of spiking neurons [Phys. Rev. E 111, 014422 (2025)].

Physical review. E·2026
Same journal

Disentangling the effects of many-body forces on depletion interactions.

Physical review. E·2026
Same journal

Charge transport and mode transition in dual-energy electron beam diodes.

Physical review. E·2026
Same journal

Optimization of multisite reactions in complex compartmentalized media.

Physical review. E·2026
Same journal

Origin of geometric cohesion in nonconvex granular materials: Interplay between interdigitation and rotational constraints enhancing frictional stability.

Physical review. E·2026
Same journal

Interaction of walkers with a standing Faraday wave.

Physical review. E·2026
See all related articles

Related Experiment Video

Updated: Jul 26, 2025

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.2K

Pooling probability distributions and partial information decomposition.

S J van Enk1

  • 1Department of Physics, University of Oregon, Eugene, Oregon 97403, USA.

Physical Review. E
|June 17, 2023
PubMed
Summary
This summary is machine-generated.

This study explores partial information decomposition (PID) by defining synergistic, redundant, and unique information. It proposes a novel pooling approach to resolve ambiguities in defining these information measures for multiple variables.

More Related Videos

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.6K
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.3K

Related Experiment Videos

Last Updated: Jul 26, 2025

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.2K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.6K
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.3K

Area of Science:

  • Information Theory
  • Multivariate Statistics
  • Computational Neuroscience

Background:

  • Partial Information Decomposition (PID) aims to quantify synergistic, redundant, and unique information among multiple variables.
  • Existing PID frameworks lack consensus on precise definitions for these information measures, leading to ambiguity.

Purpose of the Study:

  • To illustrate the sources of ambiguity in defining synergistic, redundant, and unique information within PID.
  • To propose a novel framework for PID based on probability distribution pooling.

Main Methods:

  • Defining information as the average reduction in uncertainty between probability distributions.
  • Interpreting synergistic information as the difference between the whole and the sum of its parts, using aggregated probability distributions.
  • Developing a lattice structure based on optimal probability distribution pooling.

Main Results:

  • The proposed pooling approach introduces a new lattice structure for PID, distinct from redundancy-based lattices.
  • This framework associates probability distributions with lattice nodes, not just average entropies.
  • Overlap between probability distributions emerges as a key quantity for characterizing synergistic and unique information.

Conclusions:

  • The study provides a method to resolve ambiguities in partial information decomposition by leveraging probability distribution pooling.
  • The proposed pooling approach offers a principled way to define synergistic and unique information, enhancing the understanding of multivariate information.
  • This work contributes a flexible framework for analyzing complex information relationships in multivariate systems.