Createspace Independent Publishing Platform
Approaches to Highly Parameterized Inversion: A Guide to Using PEST for Model-Parameter and Predictive-Uncertainty Analysis
$20.09
Createspace Independent Publishing Platform
Approaches in Highly Parameterized Inversion: bgaPEST, a Bayesian Geostatistical Approach Implementation With PEST?Documentation and Instructions
Product Code:
9781500297459
ISBN13:
9781500297459
Condition:
New
$20.09
Approaches in Highly Parameterized Inversion: bgaPEST, a Bayesian Geostatistical Approach Implementation With PEST?Documentation and Instructions
$20.09
The application bgaPEST is a highly parameterized inversion software package implementing the Bayesian Geostatistical Approach in a framework compatible with the parameter estimation suite PEST. Highly parameterized inversion refers to cases in which parameters are distributed in space or time and are correlated with one another. The Bayesian aspect of bgaPEST is related to Bayesian probability theory in which prior information about parameters is formally revised on the basis of the calibration dataset used for the inversion. Conceptually, this approach formalizes the conditionality of estimated parameters on the specific data and model available.
| Author: Marco D'Oria |
| Publisher: Createspace Independent Publishing Platform |
| Publication Date: Jun 23, 2014 |
| Number of Pages: 96 pages |
| Binding: Paperback or Softback |
| ISBN-10: 1500297453 |
| ISBN-13: 9781500297459 |
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