Source: https://www.stat.washington.edu/tilmann/publications.html
Timestamp: 2019-04-23 04:02:06+00:00

Document:
Kleiber, W., Raftery, A. E. and Gneiting, T. (2011). Geostatistical model averaging for locally calibrated probabilistic quantitative precipitation forecasting. Journal of the American Statistical Association , in press.
Gneiting, T., Sevcikova, H. and Percival, D. B. (2011). Estimators of fractal dimension: Assessing the smoothness of time series and spatial data. Statistical Science , in press.
Kleiber, W., Raftery, A. E., Baars, J., Gneiting, T., Mass, C. F. and Grimit, E. P. (2011). Locally calibrated probabilistic temperature forecasting using geostatistical model averaging and local Bayesian model averaging. Monthly Weather Review , in press.
Fraley, C., Raftery, A., Gneiting, T., Sloughter, M. and Berrocal, V. (2011). Probabilistic weather forecasting in R. R Journal , 3/1, 55-63.
Gneiting, T. (2011). Quantiles as optimal point forecasts. International Journal of Forecasting , 27, 197-207.
Gneiting, T. (2011). Making and evaluating point forecasts. Journal of the American Statistical Association , 106, 746-762.
Gneiting, T. and Ranjan, R. (2011). Comparing density forecasts using threshold and quantile weighted proper scoring rules. Journal of Business and Economic Statistics , 29, 411-422.
Bao, L., Gneiting, T., Grimit, E. P., Guttorp, P. and Raftery, A. E. (2010). Bias correction and Bayesian model averaging for ensemble forecasts of surface wind direction. Monthly Weather Review , 138, 1811-1821.
Berrocal, V., Raftery, A. E., Gneiting, T. and Steed, R. (2010). Probabilistic weather forecasting for winter road maintenance. Journal of the American Statistical Association , 105, 522-537.
Fraley, C., Raftery, A. E. and Gneiting, T. (2010). Calibrating multi-model forecast ensembles with exchangeable and missing members using Bayesian model averaging. Monthly Weather Review , 138, 190-202.
Gneiting, T. and Guttorp, P. (2010). Continuous-parameter stochastic process theory. In Handbook of Spatial Statistics , Gelfand, A. E., Diggle, P., Fuentes, M. and Guttorp, P., editors, Chapman & Hall/CRC, pp. 17-28.
Gneiting, T. and Guttorp, P. (2010). Continuous-parameter spatio-temporal processes. In Handbook of Spatial Statistics , Gelfand, A. E., Diggle, P., Fuentes, M. and Guttorp, P., editors, Chapman & Hall/CRC, pp. 427-436.
Gneiting, T., Kleiber, W. and Schlather, M. (2010). Matérn cross-covariance functions for multivariate random fields. Journal of the American Statistical Association , 105, 1167-1177.
Ranjan, R. and Gneiting, T. (2010). Combining probability forecasts. Journal of the Royal Statistical Society Series B: Statistical Methodology , 32, 71-91.
Sloughter, J. M., Gneiting, T. and Raftery, A. E. (2010). Probabilistic wind speed forecasting using ensembles and Bayesian model averaging. Journal of the American Statistical Association , 105 25-35.
Thorarinsdottir, T. L. and Gneiting, T. (2010). Probabilistic forecasts of wind speed: Ensemble model output statistics using heteroskedastic censored regression. Journal of the Royal Statistical Society Series A: Statistics in Society , 173, 371-388.
Czado, C., Gneiting, T. and Held, L. (2009). Predictive model assessment for count data. Biometrics , 65 1254-1261.
Mass, C., Joslyn, S., Pyle, J., Tewson, P., Gneiting, T., Raftery, A., Baars, J., Sloughter, J. M., Jones, D. and Fraley, C. (2009). PROBCAST: A web-based portal to mesoscale probabilistic forecasts. Bulletin of the American Meteorological Society , 90, 1009-1014.
Berrocal, V. J., Raftery, A. E. and Gneiting, T. (2008). Probabilistic quantitative precipitation field forecasting using a two-stage spatial model. Annals of Applied Statistics , 2, 1170-1193.
Gneiting, T. (2008). Editorial: Probabilistic forecasting. Journal of the Royal Statistical Society Series A: Statistics in Society , 171, 319-321.
Gneiting, T., Stanberry, L. I., Grimit, E. P., Held, L. and Johnson, N. A. (2008). Assessing probabilistic forecasts of multivariate quantities, with applications to ensemble predictions of surface winds. Test , 17, 211-235.
Gneiting, T., Stanberry, L. I., Grimit, E. P., Held, L. and Johnson, N. A. (2008). Rejoinder on: Assessing probabilistic forecasts of multivariate quantities, with applications to ensemble predictions of surface winds. Test , 17, 256-264.
Percival, D. B., Rothrock, D. A., Thorndike, A. S. and Gneiting, T. (2008). The variance of mean sea-ice thickness: Effect of long-range dependence. Journal of Geophysical Research , 113, C01004, doi:10.1029/2007JC004391.
Berrocal, V. J., Raftery, A. E. and Gneiting, T. (2007). Combining spatial statistical and ensemble information in probabilistic weather forecasts. Monthly Weather Review , 135, 1386-1402.
Gneiting, T. and Raftery, A. E. (2007). Strictly proper scoring rules, prediction, and estimation. Journal of the American Statistical Association , 102, 359-378.
Gneiting, T., Balabdaoui, F. and Raftery, A. E. (2007). Probabilistic forecasts, calibration and sharpness. Journal of the Royal Statistical Society Series B: Statistical Methodology , 69, 243-268.
Gneiting, T., Genton, M. G. and Guttorp, P. (2007). Geostatistical space-time models, stationarity, separability and full symmetry. In Finkenstadt, B., Held, L. and Isham, V. (eds.), Statistical Methods for Spatio-Temporal Systems, Chapman & Hall/CRC, Boca Raton, pp. 151-175.
Sloughter, J. M., Raftery, A. E., Gneiting, T. and Fraley, C. (2007). Probabilistic quantitative precipitation forecasting using Bayesian model averaging. Monthly Weather Review , 135, 3209-3220.
Gneiting, T., Larson, K., Westrick, K, Genton, M. G. and Aldrich, E. (2006). Calibrated probabilistic forecasting at the Stateline wind energy center: The regime-switching space-time method. Journal of the American Statistical Association , 101, 968-979.
Gneiting, T., Sevcikova, H., Percival, D. B., Schlather, M. and Jiang, Y. (2006). Fast and exact simulation of large Gaussian lattice systems in R²: Exploring the limits. Journal of Computational and Graphical Statistics , 15, 483-501.
Grimit, E. P., Gneiting, T., Berrocal, V. J. and Johnson, N. A. (2006). The continuous ranked probability score for circular variables and its application to mesoscale forecast ensemble verification. Quarterly Journal of the Royal Meteorological Society , 132, 2925-2942.
Guttorp, P. and Gneiting, T. (2006). Studies in the history of probability and statistics XLIX: On the Matérn correlation family. Biometrika , 93, 989-995.
Holzmann, H., Munk, A. and Gneiting, T. (2006). Identifiability of finite mixtures of elliptical distributions. Scandinavian Journal of Statistics , 33, 753-763.
Schlather, M. and Gneiting, T. (2006). Local approximation of variograms by covariance functions. Statistics & Probability Letters , 76, 1303-1304.
Gneiting, T. and Raftery, A. E. (2005). Weather forecasting with ensemble methods. Science , 310, 248-249.
Gneiting, T., Raftery, A. E., Westveld, A. H. and Goldman, T. (2005). Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation. Monthly Weather Review , 133, 1098-1118.
Raftery, A. E., Gneiting, T., Balabdaoui, F. and Polakowski, M. (2005). Using Bayesian model averaging to calibrate forecast ensembles. Monthly Weather Review , 133, 1155-1174.
Ehm, W., Gneiting, T. and Richards, D. (2004). Convolution roots of radial positive definite functions with compact support. Transactions of the American Mathematical Society , 356, 4655-4685.
Gel, Y., Raftery, A. E. and Gneiting, T. (2004). Calibrated probabilistic mesoscale weather field forecasting: The geostatistical output perturbation (GOP) method. Journal of the American Statistical Association , 99, 575-583.
Gel, Y., Raftery, A. E., Gneiting, T. and Berrocal, V. J. (2004). Rejoinder. Journal of the American Statistical Association , 99, 588-590.
Gneiting, T. and Schlather, M. (2004). Stochastic models that separate fractal dimension and the Hurst effect. SIAM Review , 46, 269-282.
Atmanspacher, H., Ehm, W. and Gneiting, T. (2003). Necessary and sufficient conditions for the quantum Zeno and anti-Zeno effect. Journal of Physics A: Mathematical and General , 36, 9899-9905.
Ehm, W., Genton, M. G. and Gneiting, T. (2003). Stationary covariances associated with exponentially convex functions. Bernoulli , 9, 607-615, 10, 375.
Mitra, S., Gneiting, T. and Sasvári, Z. (2003). Polynomial covariance functions on intervals. Bernoulli , 9, 229-241.
Gneiting, T. (2002). Compactly supported correlation functions. Journal of Multivariate Analysis , 83, 493-508.
Gneiting, T. (2002). Nonseparable, stationary covariance functions for space-time data. Journal of the American Statistical Association , 97, 590-600.
Gneiting, T. and Schlather, M. (2002). Space-time covariance models. In El-Shaarawi, A. H. and Piegorsch, W. W. (eds.), Encyclopedia of Environmetrics, Vol. 4. John Wiley & Sons, Chichester, pp. 2041-2045.
Dreier, I., Ehm, W., Gneiting, T. and Richards, D. (2001). Improved bounds for Laue's constant and multivariate extensions. Mathematische Nachrichten , 228, 109-122.
Gneiting, T. (2001). Curiosities of characteristic functions. Expositiones Mathematicae , 19, 359-363.
Gneiting, T. (2001). Criteria of Pólya type for radial positive definite functions. Proceedings of the American Mathematical Society , 129, 2309-2318.
Gneiting, T., Konis, K. and Richards, D. (2001). Experimental approaches to Kuttner's problem. Experimental Mathematics , 10, 117-124.
Gneiting, T., Sasvári, Z. and Schlather, M. (2001). Analogies and correspondences between variograms and covariance functions. Advances in Applied Probability , 33, 617-630.
Gneiting, T. (2000). Addendum to `Isotropic correlation functions on d-dimensional balls'. Advances in Applied Probability , 32, 960-961.
Gneiting, T. (2000). Power-law correlations, related models for long-range dependence, and their simulation. Journal of Applied Probability , 37, 1104-1109.
Gneiting, T. (2000). Kuttner's problem and a Pólya type criterion for characteristic functions. Proceedings of the American Mathematical Society , 128, 1721-1728.
Ehm, W., Gneiting, T. and Richards, D. (1999). On the uncertainty relation for positive-definite probability densities, II. Statistics , 33, 267-286.
Gneiting, T. (1999). Isotropic correlation functions on d-dimensional balls. Advances in Applied Probability , 31, 625-631.
Gneiting, T. (1999). A Pólya type criterion for radial characteristic functions in R². Expositiones Mathematicae , 17, 181-183.
Gneiting, T. (1999). On the derivatives of radial positive definite functions. Journal of Mathematical Analysis and Applications , 236, 86-93.
Gneiting, T. (1999). Radial positive definite functions generated by Euclid's hat. Journal of Multivariate Analysis , 69, 88-119.
Gneiting, T. (1999). The correlation bias for two-dimensional simulations by turning bands. Mathematical Geology , 31, 195-211.
Gneiting, T. (1999). Decomposition theorems for a -symmetric positive definite functions. Mathematische Nachrichten , 208, 117-120.
Gneiting, T. (1999). Correlation functions for atmospheric data analysis. Quarterly Journal of the Royal Meteorological Society , 125, 2449-2464.
Gneiting, T. and Sasvári, Z. (1999). The characterization problem for isotropic covariance functions. Mathematical Geology , 31, 105-111.
Gneiting, T. (1998). On the Bernstein-Hausdorff-Widder conditions for completely monotone functions. Expositiones Mathematicae , 16, 181-183.
Gneiting, T. (1998). On a -symmetric multivariate characteristic functions. Journal of Multivariate Analysis , 64, 131-147.
Gneiting, T. (1998). Closed form solutions of the two-dimensional turning bands equation. Mathematical Geology , 30, 379-390.
Gneiting, T. (1998). On the uncertainty relation for positive definite probability densities. Statistics , 31, 83-88.
Gneiting, T. (1998). Simple tests for the validity of correlation function models on the circle. Statistics & Probability Letters , 39, 119-122.
Gneiting, T. (1997). Normal scale mixtures and dual probability densities. Journal of Statistical Computation and Simulation , 59, 375-384.
Gneiting, T. (1996). Comment on `A simple and efficient space domain implementation of the turning bands method' by C. R. Dietrich. Water Resources Research , 32, 3391-3396.

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