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GMDSI Notebooks
GMDSI Tutorial Notebooks
Introductions to Selected Topics
Intro to Freyberg
Intro to Regression
Intro to pyEMU
Intro to Geostatistics
Intro to Bayes
Intro to SVD
Introduction to Theory, Concepts and PEST Mechanic
Manual Trial-and-Error
PEST Basics
Automated Calibration with PEST
Calibration with Two Parameters
Multiple Observation Types
GLM and the Objective Function Response Surface
Spatial Parameterisation with Pilot Points - setup
Spatial Parameterisation with Pilot Points - run
Regularization
Intro to FOSM
Local Sensitivity and Identifiability
Global Sensitivity Analysis
Monte Carlo
Decision Support Modelling with pyEMU and PEST++
Constructing a High-Dimensional PEST Interface with pyEMU
Observation Values, Weights and Noise
Prior Monte Carlo
PEST++GLM - Calculating a Jacobian Matrix
FOSM and Data Worth
PEST++GLM - Highly-Parameterized Regularized Inversion
PEST++IES - Basics
PEST++IES - Localization
PEST++DA - Getting Ready
PEST++DA - Sequential Data Assimilation
Introductions to Selected Topics
Table of contents
Intro to Freyberg
Intro to Regression
Intro to pyEMU
Intro to Geostatistics
Intro to Bayes
Intro to SVD