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

Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

556
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
556
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

134
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
134
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

233
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,...
233
Decision Making: P-value Method01:09

Decision Making: P-value Method

5.6K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.6K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

81
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
81
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

180
Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
180

You might also read

Related Articles

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

Sort by
Same author

ShallowBKGC: a BERT-enhanced shallow neural network model for knowledge graph completion.

PeerJ. Computer science·2024
Same author

Most influential countries in the international medical device trade: Network-based analysis.

Physica A·2022
Same author

Transcriptomic, Proteomic, and Metabolic Profiles of <i>Catalpa bungei</i> Tension Wood Reveal New Insight Into Lignin Biosynthesis Involving Transcription Factor Regulation.

Frontiers in plant science·2021
Same author

Nocardioides lacusdianchii sp. nov., an attached bacterium of Microcystis aeruginosa.

Antonie van Leeuwenhoek·2021
Same author

Elucidation of the anti-inflammatory mechanism of Er Miao San by integrative approach of network pharmacology and experimental verification.

Pharmacological research·2021
Same author

THE Impact of Disruption on the Relationship Between Exploitation, Exploration, and Organizational Adaptation.

Frontiers in sociology·2021
Same journal

Modeling and analysis of forward and inverse kinematics for a flexible Stewart platform.

PloS one·2026
Same journal

Barriers and facilitators to healthcare utilization amongst people living with sickle cell disease in the United States: A scoping review.

PloS one·2026
Same journal

Enhancing data completeness in time series: Imputation strategies for missing data using significant periodically correlated components.

PloS one·2026
Same journal

Key targets and mechanisms by which gut microbiota-derived metabolites regulate Alzheimer's disease through the immune - inflammatory pathway: Based on network pharmacology and molecular docking.

PloS one·2026
Same journal

Grid-tied Transformer-less Boost Switched Capacitor Topology (TLBSCT) for PV applications.

PloS one·2026
Same journal

The load-velocity profiles and exercise-specific velocity zones for seven commonly used weightlifting exercises.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Aug 28, 2025

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

12.2K

Multi-period uncertain portfolio selection model with prospect utility function.

Gaohuizi Guo1, Yao Xiao1, Cuiyou Yao1

  • 1School of Management and Engineering, Capital University of Economics and Business, Beijing, China.

Plos One
|September 14, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces an uncertain multi-period portfolio optimization model incorporating prospect theory and transaction costs. An enhanced artificial bee colony algorithm effectively solves this complex financial decision-making problem.

More Related Videos

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.2K
Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.3K

Related Experiment Videos

Last Updated: Aug 28, 2025

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

12.2K
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.2K
Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.3K

Area of Science:

  • Finance
  • Decision Science
  • Operations Research

Background:

  • Traditional portfolio optimization often overlooks investor behavior and real-world constraints.
  • Uncertainty theory and prospect theory offer more realistic frameworks for financial modeling.
  • Incorporating transaction costs and bankruptcy risk enhances model applicability.

Purpose of the Study:

  • To develop an uncertain multi-period portfolio selection model.
  • To integrate prospect theory utility and uncertain semivariance for risk and return measurement.
  • To address transaction costs and investor bankruptcy within the model.

Main Methods:

  • Formulation of an uncertain multi-period portfolio optimization model.
  • Application of prospect theory utility function and uncertain semivariance.
  • Development of a hybrid artificial bee colony algorithm with sine cosine search.

Main Results:

  • The proposed model realistically incorporates transaction costs and bankruptcy risk.
  • The novel artificial bee colony algorithm effectively solves the complex optimization problem.
  • Numerical experiments validate the model's performance and the algorithm's efficiency.

Conclusions:

  • The developed uncertain portfolio optimization model provides a more robust approach to financial decision-making.
  • The hybrid algorithm offers an effective computational tool for solving such complex problems.
  • This research contributes to more realistic and effective investment strategies under uncertainty.