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

What is Variation?01:14

What is Variation?

19.3K
Apart from the measures of central tendency, distribution, outliers, and the changing characteristics of data with time, an important characteristic of any data set is its variation or spread. In some data sets, the data values are concentrated closely near the mean; in others, the data values are more widely spread out from the mean.
The range, standard deviation, standard error, and variance are the different measures of variation.
Range: The range is the difference between its maximum and...
19.3K
Variation01:19

Variation

8.3K
An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
8.3K
Ecological Disturbance02:26

Ecological Disturbance

21.5K
An ecological disturbance is a temporary disruption in the environment resulting from abiotic, biotic, or anthropogenic factors, causing a pronounced change in an ecosystem. The impact of an ecological disturbance, which can depend on its intensity, frequency, and spatial distribution, plays a significant role in shaping the species diversity within the ecosystem.
21.5K
Entropy Changes Accompanying Specific Processes01:21

Entropy Changes Accompanying Specific Processes

101
Entropy, a measure of disorder in a system, changes during phase transitions like freezing or boiling. At the transition temperature Ttrs, where two phases are in equilibrium, the phase transition is a reversible process. The entropy change can be calculated from a substance's enthalpy of transition using the equation ΔStrs = ΔtrsH /Ttrs.When a perfect gas expands isothermally from one volume to another, entropy increases logarithmically with volume. Conversely, isothermal compression...
101
Variability: Analysis01:11

Variability: Analysis

666
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
666
Forced Oscillations01:06

Forced Oscillations

8.2K
When an oscillator is forced with a periodic driving force, the motion may seem chaotic. The motions of such oscillators are known as transients. After the transients die out, the oscillator reaches a steady state, where the motion is periodic, and the displacement is determined.
8.2K

You might also read

Related Articles

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

Sort by
Same author

Virtual reality-based cognitive-motor training in middle-aged adults at high Alzheimer's disease risk improves frontal cortex cerebral blood flow: A randomized controlled trial.

Alzheimer's & dementia (New York, N. Y.)·2026
Same author

Temporal tissue dynamics from a spatial snapshot.

Nature·2026
Same author

A foundation model for continuous glucose monitoring data.

Nature·2026
Same author

Developing Topics.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

The role of cerebrovascular reactivity on brain activation during a working memory task in type 2 diabetes.

Alzheimer's & dementia (Amsterdam, Netherlands)·2025
Same author

Distinct homotopic functional connectivity patterns of the amygdalar sub-regions as biomarkers in major depressive disorder.

Journal of affective disorders·2024
Same journal

Relation DETR+: Exploring Explicit Position Relation Prior for Dense Prediction.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

CAFE: Cross-View Adaptive Fusion and Cluster Center Enhancement for Robust Multi-View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Learning Shape Anchors for Holistic Indoor Scene Understanding.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles

Related Experiment Video

Updated: Apr 4, 2026

Experimental Methods to Study Human Postural Control
08:12

Experimental Methods to Study Human Postural Control

Published on: September 11, 2019

10.2K

The Perturbed Variation.

Maayan Harel, Shie Mannor

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |September 10, 2015
    PubMed
    Summary
    This summary is machine-generated.

    We developed Perturbed Variation (PV), a novel measure to quantify distribution similarity. This intuitive method optimally adjusts distributions to best fit each other, proving effective in various applications.

    More Related Videos

    Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns
    09:42

    Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns

    Published on: May 12, 2019

    6.5K
    Following the Dynamics of Structural Variants in Experimentally Evolved Populations
    04:52

    Following the Dynamics of Structural Variants in Experimentally Evolved Populations

    Published on: February 3, 2023

    1.4K

    Related Experiment Videos

    Last Updated: Apr 4, 2026

    Experimental Methods to Study Human Postural Control
    08:12

    Experimental Methods to Study Human Postural Control

    Published on: September 11, 2019

    10.2K
    Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns
    09:42

    Stimulus-specific Cortical Visual Evoked Potential Morphological Patterns

    Published on: May 12, 2019

    6.5K
    Following the Dynamics of Structural Variants in Experimentally Evolved Populations
    04:52

    Following the Dynamics of Structural Variants in Experimentally Evolved Populations

    Published on: February 3, 2023

    1.4K

    Area of Science:

    • Statistics
    • Machine Learning
    • Data Science

    Background:

    • Assessing similarity between probability distributions is crucial in various data analysis tasks.
    • Existing measures may lack intuitive interpretation or efficient estimation from samples.

    Purpose of the Study:

    • Introduce a new discrepancy measure, Perturbed Variation (PV), for quantifying distribution similarity.
    • Provide theoretical guarantees and demonstrate practical applications of the PV measure.

    Main Methods:

    • Define PV for continuous and discrete distributions, enabling efficient sample-based estimation.
    • Analyze convergence bounds and robustness to outliers for the PV estimator.
    • Develop a visual tracking algorithm leveraging the PV measure.

    Main Results:

    • The PV measure offers an intuitive interpretation of similarity by optimally perturbing distributions.
    • PV can be efficiently estimated from samples with proven convergence and robustness.
    • A novel visual tracking algorithm based on PV demonstrates competitive performance.

    Conclusions:

    • Perturbed Variation (PV) is a powerful and versatile new tool for distribution comparison.
    • PV's intuitive nature, efficient estimation, and robustness make it suitable for diverse applications, including visual tracking.