Approaches in Highly Parameterized Inversion

Approaches in Highly Parameterized Inversion Bgapest, a Bayesian Geostatistical Approach Implementation With Pest?documentation and Instructions

Paperback (23 Jun 2014)

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Publisher's Synopsis

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.

Book information

ISBN: 9781500297459
Publisher: Createspace Independent Publishing Platform
Imprint: Createspace Independent Publishing Platform
Pub date:
Language: English
Number of pages: 96
Weight: 244g
Height: 280mm
Width: 216mm
Spine width: 5mm