Related Experiment Video
Updated: Mar 26, 2026
12:39
A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Published on: December 10, 2012
11.7K
Contaminant source reconstruction by empirical Bayes and Akaike's Bayesian Information Criterion
Andrea Zanini1, Allan D Woodbury1
1Department of Civil Environmental Land Management Engineering and Architecture, University of Parma, Parma, Italy; Department of Civil Engineering, University of Manitoba, Winnipeg, Manitoba, Canada.
Journal of Contaminant Hydrology
|February 3, 2016
Summary
This study introduces an empirical Bayesian method with Akaike
Area of Science:
- Environmental Science
- Hydrogeology
- Statistical Modeling
Background:
- Estimating contaminant release history from limited groundwater concentration data is crucial for environmental risk assessment.
- Traditional methods may lack robustness when dealing with sparse data and complex contaminant transport.
- Bayesian approaches offer a framework to incorporate prior knowledge and quantify uncertainty in parameter estimation.
Purpose of the Study:
- To develop and validate an empirical Bayesian method using Akaike's Bayesian Information Criterion (ABIC) for estimating contaminant release histories.
- To assess the method's performance under various conditions, including different release scenarios, spatial/temporal data sparsity, and measurement errors.
- To compare the proposed method with existing geostatistical approaches.
Main Methods:
- An empirical Bayesian approach is employed, integrating prior information (Gaussian distribution, covariance function) via ABIC.
- The method estimates unknown statistical quantities like noise variance and covariance parameters.
- Confidence intervals are generated to quantify estimation error.
Main Results:
- The method successfully estimated contaminant release histories in 1D homogeneous media (Skaggs and Kabala, sharp releases) and a 2D homogeneous unconfined aquifer.
- Performance was evaluated using Gaussian and exponential covariance functions, demonstrating robustness even with large measurement errors.
- Results showed good agreement and provided valuable uncertainty quantification compared to the Kitanidis (1995) geostatistical approach.
Conclusions:
- The proposed empirical Bayesian-ABIC method is effective for reconstructing contaminant release histories from limited groundwater monitoring data.
- It provides reliable estimation and uncertainty quantification, outperforming or matching existing geostatistical techniques.
- This approach offers a valuable tool for environmental site characterization and remediation planning.
Related Concept Videos
01:24One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
1.4K
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...
On...
1.4K
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
321
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...
321
01:16Contaminants and Errors
535
Effective sample preparation is crucial for accurate and reliable laboratory analysis. During this process, two significant sources of error can arise: concentration bias from improper sample splitting and contamination caused by methods used to reduce particle size, such as grinding or homogenization. Identifying and minimizing these potential errors is crucial to ensuring the validity of the analysis.
Another key consideration is determining the appropriate number of samples required to...
Another key consideration is determining the appropriate number of samples required to...
535
01:10Propagation of Uncertainty from Systematic Error
1.6K
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
1.6K
01:18Steps in Outbreak Investigation
694
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
694
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
522
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
522