Organizer: Royal Statistical Society

Venue: The Royal Statistical Society

City: London

Country: United Kingdom

Postcode: EC1Y 8LX

Description:

Presenter: Nicolas Durrande

Level: Professional

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.

This course precedes the RSS 2017 International Conference.

Event type:
  • Workshops and courses
Introduction to Kriging and the associated tools in R https://tess.elixir-europe.org/events/introduction-to-kriging-and-the-associated-tools-in-r Presenter: Nicolas Durrande Level: Professional 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. This course precedes the RSS 2017 International Conference. Royal Statistical Society The Royal Statistical Society, London, United Kingdom The Royal Statistical Society London United Kingdom EC1Y 8LX [] [] [] workshops_and_courses [] []