SEARCH

SEARCH BY CITATION

References

  • Anderson, E., Bai, Z., Bischof, C., Blackford, S., Demmel, J., Dongarra, J., et al. (1999) LAPACK Users' Guide, 3rd edn. Society for Industrial and Applied Mathematics, Philadelphia, PA. ISBN 0-89871-447-8.
  • Banerjee, S. & Gelfand, A.E. (2002) Prediction, interpolation and regression for spatially misaligned data sets. Sankhya Series A, 64, 227245.
  • Banerjee, S., Carlin, B.P. & Gelfand, A.E. (2004) Hierarchical Modeling and Analysis for Spatial Data. Chapman and Hall/CRC Press, Boca Raton, FL.
  • Baribault, T., Kobe, R.K. & Finley, A.O. (2012) Tropical tree growth is correlated with soil phosphorus, potassium, and calcium, though not for legumes. Ecological Monographs, 82, 1891203.
  • Blackford, S.L., Demmel, J., Dongarra, J., Duff, I., Hammarling, S., Henry, G., et al. (2002) An Updated Set of Basic Linear Algebra Subprograms (BLAS). Transactions on Mathematical Software, 28, 135151.
  • Buonaccorsi, J.P. (2009) Measurement Error: Models, Methods and Applications. Chapman & Hall/CRC, Boca Raton, FL.
  • Chilés, J.P. & Delfiner, P. (1999) Geostatistics: Modelling Spatial Uncertainty. Wiley, New York.
  • Cook, B.D., Corp, L.W., Nelson, R.F., Middleton, E.M., Morton, D.C., McCorkel, J.T., et al. (2013) NASA Goddard's Lidar, Hyperspectral and Thermal (G-LiHT) airborne imager. Remote Sensing, 5, 40454066.
  • Cressie, N.A.C. & Wikle, C.K. (2011) Statistics for Spatio-Temporal Data. Wiley, New York.
  • Diggle, P.J., Tawn, J.A. & Moyeed, R.A. (1998) Model-based geostatistics (with discussion). Journal of the Royal Statistical Society, Series C (Applied Statistics), 47, 299350.
  • Finley, A.O., Banerjee, S. & Gelfand, A.E. (2013) spBayes for large univariate and multivariate point-referenced spatio-temporal data models. arXiv:1310.8192[stat.CO].
  • Finley, A.O., Banerjee, S. & Cook, B.D. (2014) Data from: Bayesian hierarchical models for spatially misaligned data in R. Methods in Ecology and Evolution. doi: 10.5061/dryad.3g9s2
  • Gelfand, A.E., Zhu, L. & Carlin, B.P. (2001) On the change of support problem for spatio-temporal data. Biostatistics, 2, 3145.
  • Gelfand, A.E., Schmidt, A.M., Banerjee, S. & Sirmans, C.F. (2004) Nonstationary multivariate process modelling through spatially varying coregionalization (with discussion). TEST, 13, 263312.
  • Gelman, A., Carlin, J.B., Stern, H.S. & Rubin, D.B. (2004) Bayesian Data Analysis, 2nd edn. Chapman and Hall/CRC Press, Boca Raton, FL.
  • Gotway, C.A. & Young, L.J. (2002) Combining incompatible spatial data. Journal of the American Statistical Association, 97, 632648.
  • Gryparis, A., Paciorek, C.J., Zeka, A., Schwartz, J. & Coull, B.A., (2009) Measurement error caused by spatial misalignment in environmental epidemiology. Biostatistics, 10, 258274.
  • Guhaniyogi, R., Finley, A.O., Banerjee, S. & Kobe, R.K. (2013) Modeling complex spatial dependencies: low-rank spatially-varying cross-covariances with application to soil nutrient data. Journal of Agricultural, Biological, and Environmental Statistics, 18, 274298.
  • Illian, J.B., Sorbye, S.H. & Rue, H. (2012) A toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA). The Annals of Applied Statistics, 6, 14991530.
  • Kamman, E.E. & Wand, M.P. (2003) Geoadditive models. Applied Statistics, 52, 118.
  • Lin, X., Wahba, G., Xiang, D., Gao, F., Klein, R. & Klein, B. (2000) Smoothing spline anova models for large data sets with Bernoulli observations and the randomized GACV. Annals of Statistics, 28, 15701600.
  • Lopiano, K.K., Young, L.J. & Gotway, C.A. (2011) A comparison of errors in variables methods for use in regression models with spatially misaligned data. Statistical Methods in Medical Research, 20, 2947.
  • Lopiano, K.K., Young, L.J. & Gotway, C.A. (2013) Estimated generalized least squares in spatially misaligned regression models with berkson error. Biostatistics, 4, 737751.
  • Madsen, L., Ruppert, D. & Altman, N.S. 2008. Regression with spatially misaligned data. Environmetrics, 19, 453467.
  • Mateu, J. & Müller, W.G. (2013) Spatio-Temporal Design: Advances in Efficient Data Acquisition. John Wiley & Sons, Ltd., West Sussex.
  • Mugglin, A.S., Carlin, B.P. & Gelfand, A.E. (2000) Fully model-based approaches for spatially misaligned data. Journal of the American Statistical Association, 95, 877887.
  • Ovaskainen, O., Hottola, J. & Siitonen, J. (2010) Modeling species co-occurrence by multivariate logistic regression generates new hypotheses on fungal interactions. Ecology, 20, 25142521.
  • Paciorek, C.J., Yanosky, J.D., Puett, R.C., Laden, F. & Suh, H.H. (2009) Practical large-scale spatio-temporal modeling of particulate matter concentrations. The Annals of Applied Statistics, 3, 370397.
  • Ren, Q. & Banerjee, S. (2013) Hierarchical factor models for large spatially misaligned data: a low-rank predictive process approach. Biometrics, 69, 1930.
  • Swope, S.M. & Parker, I.M. (2012) Complex interactions among biocontrol agents, pollinators, and an invasive weed: a structural equation modeling approach. Ecology, 22, 21222134.
  • Szpiro, A.A., Sheppard, L. & Lumley, T. (2011) Efficient measurement error correction with spatially misaligned data. Biostatistics, 12, 610623.
  • Zhu, L., Carlin, B.P. & Gelfand, A.E. (2003) Hierarchical regression with misaligned spatial data: relating ambient ozone and pediatric asthma er visits in atlanta. Environmetrics, 14, 537557.