Baker, RD and Jackson, D 2014, 'Statistical application of barycentric rational interpolants: An alternative to splines' , Computational Statistics and Data Analysis , pp. 1-17.
- Published Version
Restricted to Repository staff only
Download (880kB) | Request a copy
Spline curves, originally developed by numerical analysts for interpolation, are widely used in statistical work, mainly as regression splines and smoothing splines. Barycentric rational interpolants have recently been developed by numerical analysts, but have yet seen very few statistical applications. We give the necesssary information to enable the reader to use barycentric rational interpolants, including a suggestion for a Bayesian prior distribution, and explore the possible statistical use of barycentric interpolants as an alternative to splines. We give the all the necessary formulae, compare the numerical accuracy to splines for some Monte-Carlo datasets, and apply both regression splines and barycentric interpolants to two real datasets.We also discuss the application of these interpolants to data smoothing, where smoothing splines would normally be used, and exemplify the use of smoothing interpolants with another real dataset. Our conclusion is that barycentric interpolants are as accurate as splines, and no more difficult to understand and program. They offer a viable alternative methodology.
|Themes:||Subjects outside of the University Themes|
|Schools:||Schools > Salford Business School
Schools > Salford Business School > Business and Management Research Centre
|Journal or Publication Title:||Computational Statistics and Data Analysis|
|Funders:||Non funded research|
|Depositing User:||Prof Rose Dawn Baker|
|Date Deposited:||21 Feb 2014 14:19|
|Last Modified:||08 Nov 2015 23:04|
Actions (login required)
|Edit record (repository staff only)|