Laboratory: Geospatial Lab
My general interests lie in the fields of natural resource inventory, Bayesian statistics, spatial statistics, and statistical computing. In terms of application areas, my research focuses on spatio-temporal modeling of important economic and ecological forest attributes, indices of biodiversity, and ecological systems. A central theme in my research is the use of hierarchical models to integrate information from disparate sources to improve inference and predictions.
Selected Publication (Complete list of publications)
Finley, A.O., S. Banerjee, A.E. Gelfand. (2012) Bayesian dynamic modeling for large space-time datasets using Gaussian predictive processes. Journal of Geographical Systems, 14:29-47.
Eidsvik, J., A.O. Finley, S. Banerjee, and H. Rue. (2012) Approximate Bayesian inference for large spatial datasets using predictive process models. Computational Statistics and Data Analysis, 56: 1362-1380.
Finley, A.O., S. Banerjee, and B. Basso. (2011) Improving crop model inference through Bayesian melding with spatially-varying parameters.Journal of Agricultural, Biological, and Environmental Statistics, 16:453-474.
Guhaniyogi, R., A.O. Finley, S. Banerjee, A.E. Gelfand. (2011) Adaptive Gaussian predictive process models for large spatial datasets.Environmetrics, 22:997-1007.
Finley, A.O., S. Banerjee, and D.W. MacFarlane. (2011) A hierarchical model for quantifying forest variables over large heterogeneous landscapes with uncertain forest areas. Journal of the American Statistical Association, 106:31-48.
Finley, A.O. (2011) Comparing spatially-varying coefficients models for analysis of ecological data with non-stationary and anisotropic residual dependence. Methods in Ecology and Evolution, 2:143-154.
Banerjee, S., A.O. Finley, P. Waldmann, and T. Ericsson. (2010) Hierarchical spatial process models for multiple traits in large genetic trials. Journal of the American Statistical Association, 105:506-521.
Finley, A.O., S. Banerjee, and R.E. McRoberts. (2009) Hierarchical spatial models for predicting tree species assemblages across large domains. Annals of Applied Statistics, 3:1052-1079.
Finley, A.O., H. Sang, S. Banerjee, and A.E. Gelfand. (2009) Improving the performance of predictive process modeling for large datasets.Computational Statistics and Data Analysis, 53:2873-2884.
Finley, A.O., S. Banerjee, P. Waldmann, and T. Ericsson. (2009) Hierarchical spatial modeling of additive and dominance genetic variance for large spatial trial datasets. Biometrics, 65, 441-451.
MSU researchers investigate changes in the composition and structure of western forests
Published on January 19, 2021
Collecting, analyzing and processing 'big data'
Published on February 22, 2018