Statistical applications of the complex-step method of numerical differentiation

Ridout, Martin S. (2009) Statistical applications of the complex-step method of numerical differentiation. American Statistician, 63 (1). pp. 66-74. ISSN 0003-1305. (doi:https://doi.org/10.1198/tast.2009.0013) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)

Official URL http://dx.doi.org/10.1198/tast.2009.0013

Abstract

The complex-step method is a clever way of obtaining a numerical approximation to the first derivative of a function, avoiding the round-off error that plagues standard finite difference approximations. An extension of the method allows second derivatives to be calculated with reduced round-off error. This article provides an overview of the method, discusses its practical implementation, with particular reference to R, and studies its effectiveness in several statistical examples.

Item Type:	Article
Subjects:	Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions:	Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Statistics Faculties > Sciences > School of Mathematics Statistics and Actuarial Science
Depositing User:	Martin S Ridout
Date Deposited:	29 Jun 2011 13:54 UTC
Last Modified:	04 Jun 2014 11:06 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/24238 (The current URI for this page, for reference purposes)