8 papers
Clustering the Nearest Neighbor Gaussian Process
Ashlynn Crisp, Daniel Taylor-Rodriguez, Andrew O. Finley
Gaussian processes are ubiquitous as the primary tool for modeling spatial data. However, the Gaussian process is limited by its cost, making direct parameter fi…
A spatio-temporal statistical model for property valuation at country-scale with adjustments for regional submarkets
Brian O'Donovan, Andrew Finley, James Sweeney
Valuing residential property is inherently complex, requiring consideration of numerous environmental, economic, and property-specific factors. These complexities present significa…
Hierarchical models for small area estimation using zero-inflated forest inventory variables: comparison and implementation
Grayson W. White, Andrew O. Finley, Josh K. Yamamoto +5
National Forest Inventory (NFI) data are typically limited to sparse networks of sample locations due to cost constraints. While design-based estimators provide reliable forest par…
Multivariate spatial models for small area estimation of species-specific forest inventory parameters
Jeffrey W. Doser, Malcolm S. Itter, Grant M. Domke +1
National Forest Inventories (NFIs) provide statistically reliable information on forest resources at national and other large spatial scales. As forest management and conservation…
Spatial-temporal prediction of forest attributes using latent Gaussian models and inventory data
Paul B. May, Andrew O. Finley
The USDA Forest Inventory and Analysis (FIA) program conducts a national forest inventory for the United States through a network of permanent field plots. FIA produces estimates o…
Leveraging national forest inventory data to estimate forest carbon density status and trends for small areas
Elliot S. Shannon, Andrew O. Finley, Paul B. May +5
National forest inventory (NFI) data are often costly to collect, which inhibits efforts to estimate parameters of interest for small spatial, temporal, or biophysical domains. Tra…