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- Parker, Ryan J.; Reich, Brian J.; Eidsvik, Jo
- Journal of agricultural, biological, and environmental statistics 2016 v.21 no.3 pp. 569-587
- algorithms; coasts; covariance; data collection; ozone; spatial data; troposphere; United States
- ... Spatial data are increasing in size and complexity due to technological advances. For an analysis of a large and diverse spatial domain, simplifying assumptions such as stationarity are questionable and standard computational algorithms are inadequate. In this paper, we propose a computationally efficient method to estimate a nonstationary covariance function. We partition the spatial domain into ...
- Acosta, Jonathan; Osorio, Felipe; Vallejos, Ronny
- Journal of agricultural, biological, and environmental statistics 2016 v.21 no.3 pp. 407-425
- algorithms; autocorrelation; covariance; equations; kriging; macroalgae; models; regression analysis; variance
- ... This paper provides a framework for estimating the effective sample size in a spatial regression model context when the data have been sampled using a line transect scheme and there is an evident serial correlation due to the chronological order in which the observations were collected. We propose a linear regression model with a partially linear covariance structure to address the computation of ...