Skip to main content
padlock icon - secure page this page is secure

Fixed rank kriging for very large spatial data sets

Buy Article:

$52.00 + tax (Refund Policy)

Summary. 

Spatial statistics for very large spatial data sets is challenging. The size of the data set, n, causes problems in computing optimal spatial predictors such as kriging, since its computational cost is of order . In addition, a large data set is often defined on a large spatial domain, so the spatial process of interest typically exhibits non-stationary behaviour over that domain. A flexible family of non-stationary covariance functions is defined by using a set of basis functions that is fixed in number, which leads to a spatial prediction method that we call fixed rank kriging. Specifically, fixed rank kriging is kriging within this class of non-stationary covariance functions. It relies on computational simplifications when n is very large, for obtaining the spatial best linear unbiased predictor and its mean-squared prediction error for a hidden spatial process. A method based on minimizing a weighted Frobenius norm yields best estimators of the covariance function parameters, which are then substituted into the fixed rank kriging equations. The new methodology is applied to a very large data set of total column ozone data, observed over the entire globe, where n is of the order of hundreds of thousands.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Keywords: Best linear unbiased predictor; Covariance function; Frobenius norm; Geostatistics; Mean-squared prediction error; Non-stationarity; Remote sensing; Spatial prediction; Total column ozone

Document Type: Research Article

Affiliations: 1: The Ohio State University, Columbus, USA 2: Lawrence Livermore National Laboratory, Livermore, USA

Publication date: February 1, 2008

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more