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:
https://events.rss.org.uk/rss/120/home
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