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

Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

464
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
464
Partial Fractions01:28

Partial Fractions

163
A partial fraction is a component of a rational expression represented as the sum of simpler fractions. When a rational function is expressed as a ratio of two polynomials, it can often be decomposed into a sum of fractions whose denominators are simpler polynomials, typically linear or irreducible quadratic factors. This process is called partial fraction decomposition, and it is used to simplify complex expressions for integration, solving equations, or analysis.Partial fraction decomposition...
163
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

362
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
362
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

252
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
252
Noncompartmental Analysis: Statistical Moment Theory00:56

Noncompartmental Analysis: Statistical Moment Theory

348
Noncompartmental analyses leverage statistical moment theory to examine time-related changes in macroscopic events, encapsulating the collective outcomes stemming from the constituent elements in play. Statistical moment theory is a mathematical approach used to describe the time course of drug concentration in the body without assuming a specific compartmental model. SMT provides insights into drug absorption, distribution, metabolism, and elimination by treating drug concentration versus time...
348
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

469
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
469

You might also read

Related Articles

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

Sort by
Same author

Bayesian Multifractal Image Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2025
Same author

Efficient near-field ptychography reconstruction using the Hessian operator.

Optics express·2025
Same author

A bivariate multifractal analysis approach to understanding socio-spatial segregation dynamics.

Scientific reports·2025
Same author

Editorial: Fetal-maternal monitoring in the age of artificial intelligence and computer-aided decision support: A multidisciplinary perspective.

Frontiers in pediatrics·2022
Same author

Drowsiness detection from polysomnographic data using multivariate selfsimilarity and eigen-wavelet analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2022
Same author

Temporal evolution of the Covid19 pandemic reproduction number: Estimations from proximal optimization to Monte Carlo sampling.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2022
Same journal

Computational modelling distinguishes diverse contributors to aneurysmal progression in the Marfan aorta.

Proceedings. Mathematical, physical, and engineering sciences·2025
Same journal

Inferring the shape of data: a probabilistic framework for analysing experiments in the natural sciences.

Proceedings. Mathematical, physical, and engineering sciences·2023
Same journal

The Elbert range of magnetostrophic convection. I. Linear theory.

Proceedings. Mathematical, physical, and engineering sciences·2022
Same journal

Soft wetting with (a)symmetric Shuttleworth effect.

Proceedings. Mathematical, physical, and engineering sciences·2022
Same journal

The quantum theory of time: a calculus for q-numbers.

Proceedings. Mathematical, physical, and engineering sciences·2022
Same journal

Integrable nonlinear evolution equations in three spatial dimensions.

Proceedings. Mathematical, physical, and engineering sciences·2022
See all related articles

Related Experiment Video

Updated: Jan 5, 2026

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy
05:24

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy

Published on: January 10, 2025

724

Multifractal formalisms for multivariate analysis.

Stéphane Jaffard1, Stéphane Seuret1, Herwig Wendt2

  • 1LAMA, Univ Paris Est Creteil, Univ Gustave Eiffel, UPEM, CNRS, 94010 Créteil, France.

Proceedings. Mathematical, Physical, and Engineering Sciences
|October 16, 2019
PubMed
Summary
This summary is machine-generated.

Multivariate multifractal analysis, essential for analyzing multiple signals, faces theoretical challenges. This study reveals limitations in the standard extension and proposes improved formulations for complex data analysis.

Keywords:
multifractal multivariate formalismmultiplicative cascadesspatial regularity correlationswavelet leaders

More Related Videos

Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

20.4K
Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.3K

Related Experiment Videos

Last Updated: Jan 5, 2026

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy
05:24

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy

Published on: January 10, 2025

724
Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

20.4K
Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.3K

Area of Science:

  • Signal Processing
  • Image Analysis
  • Time Series Analysis

Background:

  • Multifractal analysis quantifies signal/texture regularity fluctuations.
  • Univariate multifractal analysis is widely used but limited to single data sources.
  • Multivariate (joint) multifractal analysis is theoretically underdeveloped and rarely applied.

Purpose of the Study:

  • To theoretically establish multivariate multifractal analysis.
  • To investigate the properties and limitations of the most direct extension of univariate methods.
  • To address the limitations of current multivariate multifractal analysis techniques.

Main Methods:

  • Theoretical investigation of multivariate multifractal analysis extensions.
  • Analysis of model processes to assess the validity of the natural extension.
  • Development and examination of alternative mathematical formulations.

Main Results:

  • The natural extension of univariate multifractal analysis to multivariate data is not universally valid.
  • Specific model processes demonstrate the success of the standard extension.
  • The study identifies mechanisms causing the failure of the natural extension.

Conclusions:

  • A direct extension of univariate multifractal analysis is insufficient for general multivariate data.
  • Alternative formulations are proposed to overcome the limitations of existing methods.
  • Further research is needed to refine and validate new multivariate multifractal analysis techniques.