Skip to main content
placeholder image

Prediction of Spatial Cumulative Distribution Functions Using Subsampling

Journal Article


Abstract


  • The spatial cumulative distribution function (SCDF) is a random function that provides a statistical summary of a random field over a spatial domain of interest. In this article we develop a spatial subsampling method for predicting an SCDF based on observations made on a hexagonal grid, similar to the one used in the Environmental Monitoring and Assessment Program of the U.S. Environmental Protection Agency. We show that under quite general conditions, the proposed subsampling method provides accurate data-based approximations to the sampling distributions of various functionals of the SCDF predictor. In particular, it produces estimators of different population characteristics, such as the quantiles and weighted mean integrated squared errors of the empirical predictor. As an illustration, we apply the subsampling method to construct large-sample prediction bands for the SCDF of an ecological index for foliage condition of red maple trees in the state of Maine. © 1999 Taylor & Francis Group, LLC.

Publication Date


  • 1999

Citation


  • Lahiri, S. N., Kaiser, M. S., Cressie, N., & Hsu, N. J. (1999). Prediction of Spatial Cumulative Distribution Functions Using Subsampling. Journal of the American Statistical Association, 94(445), 86-97. doi:10.1080/01621459.1999.10473821

Scopus Eid


  • 2-s2.0-0442293854

Web Of Science Accession Number


Start Page


  • 86

End Page


  • 97

Volume


  • 94

Issue


  • 445

Abstract


  • The spatial cumulative distribution function (SCDF) is a random function that provides a statistical summary of a random field over a spatial domain of interest. In this article we develop a spatial subsampling method for predicting an SCDF based on observations made on a hexagonal grid, similar to the one used in the Environmental Monitoring and Assessment Program of the U.S. Environmental Protection Agency. We show that under quite general conditions, the proposed subsampling method provides accurate data-based approximations to the sampling distributions of various functionals of the SCDF predictor. In particular, it produces estimators of different population characteristics, such as the quantiles and weighted mean integrated squared errors of the empirical predictor. As an illustration, we apply the subsampling method to construct large-sample prediction bands for the SCDF of an ecological index for foliage condition of red maple trees in the state of Maine. © 1999 Taylor & Francis Group, LLC.

Publication Date


  • 1999

Citation


  • Lahiri, S. N., Kaiser, M. S., Cressie, N., & Hsu, N. J. (1999). Prediction of Spatial Cumulative Distribution Functions Using Subsampling. Journal of the American Statistical Association, 94(445), 86-97. doi:10.1080/01621459.1999.10473821

Scopus Eid


  • 2-s2.0-0442293854

Web Of Science Accession Number


Start Page


  • 86

End Page


  • 97

Volume


  • 94

Issue


  • 445