Featured, Upcoming webinars, Webinars

The Maths Behind PEST and PEST++

GMDSI will host three webinars. These will be delivered by John Doherty (author of PEST) in biweekly intervals. Dates are as follows: Webinar 1: Wednesday

intro to pyemu

intro_to_pyemu Intro to pyEMU¶ This notebook provides a quick run through some of the capabilities of pyemu for working with PEST(++). This run through is

Introduction to Regression

  Introduction to Regression¶ This tutorial proves an overview of linear regression. It illustrates fitting a polynomial to noisy data, including the role of SSE

Non-Linear Uncertainty Analysis

In contrast to linear uncertainty analysis, non-linear methods do not suffer from the limitation of assuming a linear relationship between model predictions and model parameters.

Covariance Matrices: The PPCOV Suite

A variance-covariance matrix, often referred to as a covariance matrix, is a square matrix that provides covariances between pairs of elements of a random vector.

Data Worth Analysis

The present tutorial addresses the ability (or otherwise) of yet-ungathered data to reduce the uncertainties of decision-critical predictions using linear analysis utilities from the PEST

Linear Uncertainty Analysis

Linear uncertainty analysis is also known as “first order second moment” (or “FOSM”) analysis. It provides approximate mathematical characterisation of prior predictive probability distributions, and