Technical note: Estimating unbiased transfer-function performances in spatially structured environments

• Main Authors: M. Trachsel, R. J. Telford
• Format: Article
• Language: English
• Published: Copernicus Publications 2016-05-01
• Series: Climate of the Past
• Online Access: http://www.clim-past.net/12/1215/2016/cp-12-1215-2016.pdf

Conventional cross validation schemes for assessing transfer-function performance assume that observations are independent. In spatially structured environments this assumption is violated, resulting in over-optimistic estimates of transfer-function performance. <i>H</i>-block cross validation, where all samples within <i>h</i> kilometres of the test samples are omitted, is a method for obtaining unbiased transfer-function performance estimates. In this study, we assess three methods for determining the optimal <i>h</i>. Using simulated data, we find that all three methods result in comparable values of <i>h</i>. Applying the three methods to published transfer functions, we find they yield similar values for <i>h</i>. Some transfer functions perform notably worse when <i>h</i>-block cross validation is used.