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Journal Articles
- F Petropoulos, D Apiletti, V Assimakopoulos, M Z Babai, D K Barrow, S B Taieb, C Bergmeir, R J Bessa, J Bijak, J E Boylan, J Browell, C Carnevale, J L Castle, P Cirillo, M P Clements, C Cordeiro, F L C Oliveira, S de Baets, A Dokumentov, J Ellison, P Fiszeder, P H Franses, D T Frazier, M Gilliland, M S Gönül, P Goodwin, L Grossi, Y Grushka-Cockayne, M Guidolin, M Guidolin, U Gunter, X Guo, R Guseo, N Harvey, D F Hendry, R Hollyman, T Januschowski, J Jeon, V R R Jose, Y Kang, A B Koehler, S Kolassa, N Kourentzes, S Leva, F Li, K Litsiou, S Makridakis, G M Martin, A B Martinez, S Meeran, T Modis, K Nikolopoulos, D Önkal, A Paccagnini, A Panagiotelis, I Panapakidis, J M Pavía, M Pedio, D J Pedregal, P Pinson, P Ramos, D E Rapach, J J Reade, B Rostami-Tabar, M Rubaszek, G Sermpinis, H L Shang, E Spiliotis, A A Syntetos, P D Talagala, T S Talagala, L Tashman, D Thomakos, T Thorarinsdottir, E Todini, J R T Arenas, X Wang, R L Winkler, A Yusupova and F Ziel
Forecasting: theory and practice
International Journal of Forecasting, in press, 2022 [http] - S M Vandeskog, T L Thorarinsdottir, I Steinsland and F Lindgren
Quantile based modelling of diurnal temperature range with the five-parameter lambda distribution
Environmetrics, 33(4): e2719, 2022 [http] - T Roksvåg, J Lutz, L Grinde, A V Dyrrdal and T L Thorarinsdottir
Consistent intensity-duration-frequency curves by post-processing of estimated Bayesian posterior quantiles
Journal of Hydrology, 603(C):127000, 2021 [http] - Q Yuan, T L Thorarinsdottir, S Beldring, W K Wong and C-Y Xu
Bridging the scale gap: obtaining high-resolution stochastic simulations of gridded daily precipitation in a future climate
Hydrology and Earth System Sciences, 25: 5259-5275, 2021 [http] - F Krürger, S Lerch, T L Thorarinsdottir and T Gneiting
Predictive inference based on Markov chain Monte Carlo output
International Statistical Review, 89(2): 274-301, 2021 [http | arxiv] - C Heinrich, K H Hellton, A Lenkoski and T L Thorarinsdottir
Multivariate postprocessing methods for high-dimensional seasonal weather forecasts
Journal of the American Statistical Association, 116(535):1048-1059, 2021 [http | arxiv] - T L Thorarinsdottir, J Sillmann, M Haugen, N Gissibl and M Sandstad
Evaluation of CMIP5 and CMIP6 simulations of historical surface air temperature extremes using proper evaluation methods
Environmental Research Letters, 15:124041, 2020 [http] - M Jullum, T L Thorarinsdottir and F E Bachl
Estimating seal pup production in the Greenland Sea using Bayesian hierarchical modeling
Journal of the Royal Statistical Society, Series C, 69(2): 327-352, 2020 [http | arxiv] - O Haug, T L Thorarinsdottir, S H Soerbye and C L E Franzke
Spatial trend analysis of gridded temperature data at varying spatial scales
Advances in Statistical Climatology, Meteorology and Oceanography, 6: 1-12, 2020 [http | arxiv] - N Schuhen, T L Thorarinsdottir and A Lenkoski
Rapid adjustment and post-processing of temperature forecast trajectories
Quarterly Journal of the Royal Meteorological Society, 146: 963-978, 2020 [http | arxiv] - Q Yuan, T L Thorarinsdottir, S Beldring, W K Wong, S Huang and C-Y Xu
New approach for bias correction and stochastic downscaling of future projections for daily mean temperatures to a high-resolution grid
Journal of Applied Meteorology and Climatology, 58: 2617-2632, 2019 [http | arxiv] - T L Thorarinsdottir, K H Hellton, G H Steinbakk, L Schlichting and K Engeland
Bayesian regional flood frequency analysis for large catchments
Water Resources Research, 54(9): 6929-6947, 2018 [http] - P Guttorp and T L Thorarinsdottir
How to save Bergen from the sea? Decisions under uncertainty
Significance, 15(2): 14-18, 2018 [pdf] - F Kobierska, K Engeland and T L Thorarinsdottir
Evaluation of design flood estimates -- a case study for Norway
Hydrology Research, 49(2): 450-465, 2017 [preprint | http] - J Sillmann, T Thorarinsdottir, N Keenlyside, N Schaller, L V Alexander, G Hegerl, S I Seneviratne, R Vautard, X Zhang and F W Zwiers
Understanding, modeling and predictig weather and climate extremes: Challenges and opportunities
Weather and Climate Extremes, 18: 65-74, 2017 [pdf | http] - T L Thorarinsdottir, P Guttorp, M Drews, P Skougaard Kaspersen and K de Bruin
Sea level adaptation decisions under uncertainty
Water Resources Research, 53(10): 8147-8163, 2017 [tech | http] - R Benestad, J Sillmann, T L Thorarinsdottir, P Guttorp, M d S Mesquita, M R Tye, P Uotila, C Fox Maule, P Thejll, M Drews and K M Parding
New vigour involving statisticians to overcome ensemble fatigue
Nature Climate Change, 7: 697-703, 2017 [http] - S Lerch, T L Thorarinsdottir, F Ravazzolo and T Gneiting
Forecaster's dilemma: Extreme events and forecast evaluation
Statistical Science, 32(1): 106-127, 2017 [bib | arxiv | http] - G H Steinbakk, T L Thorarinsdottir, T Reitan, L Schlichting, S Hølleland and K Engeland
Propagation of rating curve uncertainty in design flood estimation
Water Resources Research, 52(9): 6897-6915, 2016 [bib | tech | http] - T L Thorarinsdottir, M Scheuerer and C Heinz
Assessing the calibration of high-dimensional ensemble forecasts using rank histograms
Journal of Computational and Graphical Statistics, 25(1): 105-122, 2016 [bib | arxiv | http] - E-M Didden, T L Thorarinsdottir, A Lenkoski and C Schnörr
Shape from texture using locally scaled point processes
Image Analysis & Stereology, 34: 161-170, 2015 [bib | arxiv | pdf] - F E Bachl, A Lenkoski, T L Thorarinsdottir and C Garbe
Bayesian motion detection for dust areosols
Annals of Applied Statistics, 9(3): 1298-1327, 2015 [bib | arxiv | http] - L V Hansen, T L Thorarinsdottir, E Ovcharov, T Gneiting and D Richards
Gaussian random particles with flexible Hausdorff dimension
Advances in Applied Probability, 47(2): 307-327, 2015 [bib | tech | arxiv | http] - A V Dyrrdal, A Lenkoski, T L Thorarinsdottir and F Stordal
Bayesian hierarchical modeling of extreme hourly precipitation in Norway
Environmetrics, 26(2): 89-106, 2015 [bib | arxiv | http] - K Feldmann, M Scheuerer and T L Thorarinsdottir
Spatial postprocessing of ensemble forecasts for temperature using nonhomogeneous Gaussian regression
Monthly Weather Review, 143(3): 955-971, 2015 [bib | arxiv | http] - K Willett, C Williams, I Jolliffe, R Lund, L Alexander, S Brönniman, L A Vincent, S Easterbrook, V Venema, D Berry, R Warren, G Lopardo, R Auchmann, E Aguilar, M Menne, C Gallagher, Z Hausfather, T Thorarinsdottir and P W Thorne
A framework for benchmarking of homogenisation algorithm performance on the global scale
Geoscientific Instrumentation, Methods and Data Systems Discussions, 3: 187-200, 2014 [pdf] - T L Thorarinsdottir, T Gneiting and N Gissibl
Using proper divergence functions to evaluate climate models
SIAM/ASA Journal on Uncertainty Quantification, 1(1): 522-534, 2013 [bib | http | arxiv] - R Schefzik, T L Thorarinsdottir and T Gneiting
Uncertainty quantification in complex simulation models using ensemble copula coupling
Statistical Science, 28(4): 616-640, 2013 [bib | http | arxiv] - S Lerch and T L Thorarinsdottir
Comparing nonhomogeneous regression models for probabilistic wind speed forecasting
Tellus A, 65: 21206, 2013 [bib | http | arxiv] - T L Thorarinsdottir
Calibration diagnostics for point process models via the probability integral transform
Stat 2(1): 150-158, 2013 [bib | http | arxiv] - A Möller, A Lenkoski, and T L Thorarinsdottir
Multivariate probabilistic forecasting using Bayesian model averaging and copulas
Quarterly Journal of the Royal Meteorological Society, 139(673): 982-991, 2013 [bib | http | arxiv] - L V Hansen and T L Thorarinsdottir
A note on moving average models for Gaussian random fields
Statistics and Probability Letters, 83(3): 850-855, 2013 [bib | http | tech] - T L Thorarinsdottir, M Scheuerer, and K Feldmann
Statistical post-processing of ensemble forecasts
Promet, 37(3/4):43-52, 2012 (in German, invited paper) [bib | pdf] - P Friederichs and T L Thorarinsdottir
Forecast verification for extreme value distributions with an application to probabilistic peak wind prediction
Environmetrics, 23(7):579-594, 2012 [bib | http | arxiv] - N Schuhen, T L Thorarinsdottir, and T Gneiting
Ensemble model output statistics for wind vectors
Monthly Weather Review, 140(10):3204-3219, 2012 [bib | http | arxiv] - P Guttorp and T L Thorarinsdottir
What happened to discrete chaos, the Quenouille process, and the sharp Markov property? Some history of stochastic point processes
International Statistical Review, 80(2):253-268, 2012 [bib | http | tech] - T L Thorarinsdottir and M S Johnson
Probabilistic wind gust forecasting using non-homogeneous Gaussian regression
Monthly Weather Review, 140(3):889-897, 2012 [bib | http] - T L Thorarinsdottir and T Gneiting
Probabilistic forecasts of wind speed: Ensemble model output statistics by using heteroskedastic censored regression
Journal of the Royal Statistical Society Series A: Statistics in Society, 173(2):371-388, 2010 [bib | http | tech] - E B V Jensen and T L Thorarinsdottir
A spatio-temporal model for functional magnetic resonance imaging data - with a view to resting state networks
Scandinavian Journal of Statistics, 34(3):587-614, 2007 [bib | http | tech] - M H Neumann and T L Thorarinsdottir
Asymptotic minimax estimation in nonparametric autoregression
Mathematical Methods of Statistics, 15(4):374-397, 2007 [bib | pdf] - T L Thorarinsdottir
Bayesian image restoration, using configurations
Image Analysis & Stereology, 25:129-143, 2006 [bib | pdf]
- T L Thorarinsdottir and N Schuhen
Chapter 6 - Verification: assessment of calibration and accuracy
In S Vannitsem, D S Wilks and J W Messner (Eds.), Statistical Postprocessing of Ensemble Forecasts, pp. 155-186. Elsevier, 2018. [tech | http] - P Guttorp and T L Thorarinsdottir
Bayesian inference for non-Markovian point processes
In E Porcu, J M Montero, and M Schlather (Eds.), Advances and Challenges in Space-time Modelling of Natural Events, pp. 79-102. Lecture Notes in Statistics, Volume 207. Springer: Berlin Heidelberg, 2012 [bib | http | tech]
- T L Thorarinsdottir and E B V Jensen
Modelling resting state networks in the human brain
In R Lechnerová, I Saxl, and V Beneš, editors, Proceedings S4G: International Conference on Stereology, Spatial Statistics and Stochastic Geometry, pp. 137-147, 2006 [bib | pdf]
Working Papers
- T Erhardt, C Czado and T L Thorarinsdottir
Evaluation of time series models under non-stationarity with application to the comparison of regional climate models
arXiv:1702.00728, 2017 [arxiv] - A Möller, T L Thorarinsdottir, A Lenkoski and T Gneiting
Spatially adaptive, Bayesian estimation for probabilistic temperature forecasts
arXiv:1507.05066, 2015 [bib | arxiv] - T Gneiting and T L Thorarinsdottir
Predicting inflation: professional experts versus no-change forecasts
arXiv:1010.2318, 2010 [bib | arxiv]
- A Lenkoski and T L Thorarinsdottir
Comments on: Of quantiles and expectiles: consistent scoring functions, Choquet representations and forecast rankings by W Ehm, T Gneiting, A Jordan and F Krüger
Journal of the Royal Statistical Society, Series B, 78(3): 548, 2016 [http] - T L Thorarinsdottir and A Løland
Comments on: Space-time wind speed forecasting for improved power system dispatch by X Zhu, M G Genton, Y Gu and L Xie
TEST, 23(1): 32-33, 2014 [bib | http]
- P Guttorp and T L Thorarinsdottir
Local climate projections: A little money goes a long way
Eos, 100, doi:10.1029/2019EO133113, 2019 [http] - T L Thorarinsdottir and K de Bruin
Challenges of climate change adaptation
Eos, 97, doi:10.1029/2016EO062121, 2016 [http]
[The full workshop report is available here] - T L Thorarinsdottir, J Sillmann and R Benestad
Studying statistical methodology in climate research
EOS Transactions, 95(15): 129, 2014 [bib | http]
Last updated May 29, 2022 by TLT