Gaussian processes for time-series modelling

Resource | v1 | created by janarez |
Edit
bookmark
Type Paper
Created 2013-02-13
Available at royalsocietypublishing.org/doi/10.1098/rsta.2011.0550
Identifier ISSN: 1364-503X, 1471-2962
Description

In this paper, we offer a gentle introduction to Gaussian processes for time-series data analysis. The conceptual framework of Bayesian modelling for time-series data is discussed and the foundations of Bayesian non-parametric modelling presented for Gaussian processes. We discuss how domain knowledge influences design of the Gaussian process models and provide case examples to highlight the approaches.

Relations

about Gaussian process

In probability theory and statistics, a Gaussian process is a stochastic process (a collection of ran...

Edit details Edit relations Attach new author Attach new topic Attach new resource
9.0 /10
useless alright awesome
from 1 review
Write comment Rate resource Tip: Rating is anonymous unless you also write a comment.
Resource level 3.0 /10
beginner intermediate advanced
Resource clarity 7.0 /10
hardly clear sometimes unclear perfectly clear
Reviewer's background 3.0 /10
none basics intermediate advanced expert
Comments 0
Currently, there aren't any comments.