Introduction to Kriging and the associated tools in R

Date:

04/09/2017

Organised by:

Royal Statistical Society

Presenter:

Nicholas Durrande

Level:

Entry (no or almost no prior knowledge)

Contact:

Tessa Pearson
training@rss.org.uk
020 7614 3947

Map:

View in Google Maps  (G1 1RD)

Venue:

Technology & Innovation Centre, University of Strathclyde, 99 George St, Glasgow

Description:

Presenter: Nicolas Durrande

Level: Foundation

CPD: 6 hours

Kriging (or Gaussian process regression) has proven to be of great interest when trying to approximate a costly function to evaluate, in a closed form. The aim of the workshop is to show how useful surrogate models can be; to detail how to build such models in R; and to make clear the assumptions these models rely on. In the morning we introduce the concepts of Kriging through lectures and lab sessions. During the afternoon we see in more detail how to tune these models and how they can be used to solve optimization problems. The aim of the afternoon lab is to quickly find the settings of a catapult numerical simulator that give the longest shot.

Cost:

288+VAT

Website and registration:

Region:

Scotland

Keywords:

Data Collection, Quantitative Data Handling and Data Analysis, ICT and Software

Related publications and presentations:

Data Collection
Quantitative Data Handling and Data Analysis
ICT and Software

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