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

Poisson's And Laplace's Equation01:25

Poisson's And Laplace's Equation

3.4K
The electric potential of the system can be calculated by relating it to the electric charge densities that give rise to the electric potential. The differential form of Gauss's law expresses the electric field's divergence in terms of the electric charge density.
3.4K
Poisson Probability Distribution01:09

Poisson Probability Distribution

8.4K
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...
8.4K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

704
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
704
Poisson's Ratio01:23

Poisson's Ratio

535
Poisson's ratio is a material property that indicates their stress response. It explains the connection between the elongation or compression a material undergoes in the direction of an applied force and the contraction or expansion it experiences perpendicular to that force. When a slender bar is loaded axially, it stretches in the direction of the force and contracts laterally. Poisson's ratio is the negative ratio of this lateral contraction to the axial elongation. The negative sign...
535
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

7.8K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
7.8K
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

589
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...
589

You might also read

Related Articles

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

Sort by
Same author

Best-subset instrumental variable selection method using mixed integer optimization with applications to health-related quality of life and education-wage analyses.

Research square·2024
Same author

LASSO-type instrumental variable selection methods with an application to Mendelian randomization.

Statistical methods in medical research·2024
Same author

A new class of efficient and debiased two-step shrinkage estimators: method and application.

Journal of applied statistics·2022
Same author

A new kind of stochastic restricted biased estimator for logistic regression model.

Journal of applied statistics·2022
Same author

Reliability Analysis of the New Exponential Inverted Topp-Leone Distribution with Applications.

Entropy (Basel, Switzerland)·2021
Same author

A New Ridge-Type Estimator for the Gamma Regression Model.

Scientifica·2021
Same journal

Elastic functional Cox regression model with shape predictors.

Journal of applied statistics·2026
Same journal

An improved two-stage binary relevance method for multilabel classification.

Journal of applied statistics·2026
Same journal

Classification of multivariate functional data with an application to ADHD fMRI data.

Journal of applied statistics·2026
Same journal

Assessing the performance of longitudinal T-lymphocytes as biomarkers of immune recovery in HIV-infected children with or without TB co-infection.

Journal of applied statistics·2026
Same journal

Sparse long-only Markowitz portfolio optimization.

Journal of applied statistics·2026
Same journal

Homogeneity of multinomial populations when data are classified into a large number of groups.

Journal of applied statistics·2026
See all related articles

Related Experiment Video

Updated: Sep 8, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K

A new Poisson Liu Regression Estimator: method and application.

Muhammad Qasim1, B M G Kibria2, Kristofer Månsson1

  • 1Department of Economics, Finance and Statistics, Jönköping University, Jönköping, Sweden.

Journal of Applied Statistics
|June 16, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces the Poisson Liu Regression Estimator (PLRE) to improve parameter estimation in Poisson regression models with multicollinearity. New shrinkage parameter estimation methods offer more precise results in simulations and empirical applications.

Keywords:
Liu estimatorMLEMSEPoisson regressionshrinkage estimatorssimulation study

More Related Videos

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
Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
10:10

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

Published on: September 18, 2021

38.4K

Related Experiment Videos

Last Updated: Sep 8, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K
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
Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
10:10

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

Published on: September 18, 2021

38.4K

Area of Science:

  • Statistics
  • Econometrics

Background:

  • Poisson regression is widely used for count data.
  • High multicollinearity can destabilize parameter estimates.

Purpose of the Study:

  • To propose and evaluate new methods for parameter estimation in Poisson regression under multicollinearity.
  • Introduce the Poisson Liu Regression Estimator (PLRE).

Main Methods:

  • Development of novel shrinkage parameter estimation approaches for PLRE.
  • Monte Carlo simulations to assess small sample properties.
  • Evaluation using Mean Square Errors (MSE) and Mean Absolute Percentage Errors (MAPE).

Main Results:

  • The proposed shrinkage parameter estimation methods demonstrate superior performance in finite samples.
  • PLRE with new estimation techniques yields more precise estimators compared to traditional methods.
  • Simulation results confirm the benefits of the proposed techniques.

Conclusions:

  • The novel shrinkage parameter estimation methods for PLRE are effective in mitigating multicollinearity issues in Poisson regression.
  • Empirical application validates the practical relevance and improved precision of the proposed techniques.