Publications

Publications

Books

  • H. Bandemer et al.: Theorie und Anwendung der Optimalen Versuchsplanung, Vol. I, Akademie-Verlag, Berlin 1977
  • J. Pilz: Bayesian Estimation and Experimental Design in Linear Regression Models. Teubner-Texte zur Mathematik, Vol. 55, BSB B.G. Teubner-Verlagsgesellschaft, Leipzig 1983
  • J. Pilz: Bayesian Estimation and Experimental Design in Linear Regression Models. Largely revised and extended license edition of the aforementioned book, John Wiley & Sons, Chichester, New York 1991
  • D. Rasch, J. Pilz, R.L. Verdooren, A. Gebhardt: Optimal Design of Experiments with R.Chapman and Hall/ CRC Press, Boca Raton 2011
  • Bo Zhao and J. Pilz: Extraction of the Ore-Caused Anomaly and Study of the Metallogenic Efficiency in (Heavily-Covered) Western Zhejiang province of China. Golden Light Academic Publishing, Beijing, 2017, ISBN: 978-620-2-41068-7
  • D. Rasch, R. Verdooren and J. Pilz: Applied Statistics. Theory and Problem Solutions in R. J. Wiley and Sons, Oxford 2020
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Edited Books and Volumes

  • J. Pilz, Ed.: Interfacing Geostatistics and GIS. Springer-Verlag, Berlin-Heidelberg 2009
  • D. Cornford, G. Dubois, D. Hristopulos, E. Pebesma, J. Pilz (Eds.): Geoinformatics for Environmental Surveillance. Special Issue of Computers & Geosciences 37 (2011) No. 3
  • J. Pilz, D. Rasch, V. Melas and K. Moder: Eds. Simulation and Statistics. 8th Int. Workshop on Simulation, Vienna 2015. Springer-Verlag, Berlin-Heidelberg 2018
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Articles

  • H. Bandemer, J. Pilz: Optimum experimental design for a Bayes estimator in linear regression. Transact. Eighth Prague Conf. on Inf. Theory, Statist. Decis. Functions and Random Processes, Vol. A, Academia Praha 1978, 93 - 102
  • J. Pilz: Bayessche Schätzung und Versuchsplanung im linearen Regressionsmodell. Dissertation A, Bergakademie Freiberg, 1978
  • J. Pilz: Entscheidungstheoretische Darstellung des Problems der Bayesschen Schätzung und Versuchsplanung im linearen Regressionsmodell. Freiberger Forschungshefte D 117, VEB Deutscher Verlag für Grundstoffindustrie, Leipzig 1979, 7 - 20
  • J. Pilz: Das Bayessche Schätzproblem im linearen Regressionsmodell. Freiberger For schungshefte D 117, VEB Deutscher Verlag für Grundstoffindustrie, Leipzig 1979, 21 - 55
  • J. Pilz: Optimalitätskriterien, Zulässigkeit und Vollständigkeit im Planungsproblem für eine Bayessche Schätzung im linearen Regressionsmodell. Freiberger Forschungshefte D 117, VEB Deutscher Verlag für Grundstoffindustrie Leipzig 1979, 67 - 94
  • J. Pilz: Konstruktion von optimalen diskreten Versuchsplänen für eine Bayes-Schätzung im linearen Regressionsmodell. Freiberger Forschungshefte D 117, VEB Deutscher Verlag für Grundstoffindustrie Leipzig 1979, 123 - 152
  • W. Näther, J. Pilz: Estimation and experimental design in a linear regression model using prior information. Zastosowania Matematyki 16 (1980), 565 - 577
  • J. Pilz: Ausnutzung von a-priori-Kenntnissen zur Schätzung und Versuchsplanung im linearen Regressionsmndell. Lehrmaterial "Mathematische Statistik in der Technik" (H. Bandemer, Ed.), Wiss. Informationszentrum Freiberg 1980, 113 - 120
  • J. Pilz: Bayessche Schätzung und Versuchsplanung für die multiple lineare Regression. IX. Int. Kongreß über Anwendungen der Mathematik in den Ingenieurwissenschaften, Heft 4, Weimar 1981, 54 - 57
  • J. Pilz: Robust Bayes and minimax-Bayes estimation and design in linear regression. Math. Operationsforsch. Stat., Ser. Statistics12 (1981), 163 - 177
 
  • J. Gladitz, J. Pilz: Construction of optimal designs in random coefficient regression models Math. Operationsforsch. Stat., Ser. Statistics 13 (1982), 371 - 385
  • J. Gladitz, J. Pilz: Bayes designs for multiple linear regression on the unit sphere. Math. Ope- rationsforsch. Stat., Ser. Statistics 13 (1982), 491 - 506
  • J. Pilz: Schätzung und Versuchsplanung für beste Regressionsgeraden bei vorgegebenen Schranken. Tagungsmaterialien der 7. Fachtagung Qualitätsanalyse, Frankfurt/Oder 1983
  • J. Pilz: Robust Bayes regression estimation under weak prior knowledge. In: Robustness of Statistical Methods and Nonparametric Statistics (Eds.: D. Rasch and M.L. Tiku), VEB Deutscher Verlag der Wissenschaften, Berlin 1984, 85 - 89
  • J. Pilz, B. Fellenberg: On the choice of prior distributions for Bayesian reliability analysis. Freiberger Forschungshefte D 170, VEB Deutscher Verlag für Grundstoffindustrie, Leipzig 1985, 49 - 68
  • J. Pilz: Minimax straight line regression estimation using prior bounds for the parameters. Freiberger Forschungshefte D 170, VEB Deutscher Verlag f'ür Grundstoffindustrie, Leipzig 1985, 33 - 48
 
  • J. Pilz: A note on Krafft's maximin linear estimator for linear regression parameters. Statistics 17(1986), 9 - 14
  • J. Pilz: Minimax linear regression estimation with symmetric parameter restrictions. J. Statist. Planning and Inference 13 (1986), 297 – 318
  • H. Bandemer, B. Fellenberg, J. Pilz: Integral geometric prior distributions for Bayesian re- gression with bounded response. Statistics 17 (1986), 323 – 335
  • J. Pilz: Beiträge zur Theorie der Bayes- und minimax-linearen Schätzungen in linearen Regressionsmodellen. DSc. Dissertation, Bergakademie Freiberg, 1987
  • H. Bandemer, W. Näther, J. Pilz: Once more: Optimal experimental designs for regression models. Statistics 18 (1987), 171 - 217
  • J. Pilz: Minimax linear approgression estimation for finite dimensional classes of regression functions. Transact. Tenth Prague Conf. on Inform. Theory, Statist. Decis. Funct. and Random Processes, Academia Praha 1988, 237 - 246
  • J. Pilz: Admissible and minimax linear estimation in linear models with compact parameter region. DFG-Schwerpunktprogramm "Anwendungsbezogene Optimierung und Steuerung“, Univ. Augsburg, Report No. 100, 1988
  • J. Pilz: Minimax estimation with ellipsoid and linear inequality constraints. DFG- Schwer- punktprogramm "Anwendungsbezogene Optimierung und Steuerung", Univ. Augsburg, Report No. 110, 1988
  • J. Pilz, A. Kühl: Rechnergestützte Methoden in der geologischen Forschung und Erkundung Tagungsbericht zum 40. Berg- und Hüttenmännischen Tag, Freiberg 1989, Neue Bergbautechnik19 (1989), 419 – 422
  • J. Pilz: Minimax linear estimation for fitting biased response surfaces. Statistics&Decisions 8 (1990), 47 - 60
  • J. Pilz: Bayes estimation of variograms and Bayesian collocation. Proc. 22nd Int. Symposium APCOM, TUB-Dokumentation, Heft 51, Band II, Berlin 1990, 565 - 576
  • J. Pilz: Das Bayessche Informationskriterium und Fragen der Modellwahl. In: Beiträge zur Mathematischen Geologie und Geoinformatik Band l (Ed.: G. Pesche.l), Verlag Sven von Loga, Köln 1991, 14 - 21
  • J. Pilz: Invited discussion paper on „Predictive inference from samples of smooth processes“ by J. V. Zidek and S. Weerahandi. In: Bayesian Statistics 4 (J. M. Bernardo et al., Eds), Oxford Univ. Press 1992
  • J. Pilz: Discussion on „Some Bayesian numerical analysis“ by A. O’Hagan. In: Bayesian Statistics 4 (J. M. Bernardo et al., Eds), Oxford Univ. Press 1992
  • J. Pilz: Bayes optimal design of monitoring networks. In: Operations Research ’91 (P. Gritzmann et al., Eds.), Physica-Verlag, Heidelberg 1992, 355 - 358
  • J. Pilz: Zur Verwendung von a-priori-Kenntnissen in geostatistischen Modellen. In: Beiträge zur Mathematischen Geologie und Geoinformatik (Ed.: G. Peschel), Verlag Sven von Loga, Köln 1992, Band 3, 2 - 11
  • J. Pilz: Some thoughts on the present position in Bayesian statistics. In: Modelling Uncertain Data (H. Bandemer, Ed.), Akademie Verlag, Berlin 1992, 70 – 82
  • J. Menz, J. Pilz: Kollokation, Universelles Kriging und Bayesscher Zugang. Das Markschei- dewesen 101 (1994) Nr. 2, 62 - 66
  • U. Dutschmann, M. Jäkel, J. Pilz: Räumliche Charakterisierung eines industriellen Alstandor- tes in Sachsen mittels geostatistischen Methoden. In: GAR-Proceedings, TU Bergakademie Freiberg 1994, 23 - 29
  • J. Pilz: Vergleich verschiedener Strategien zur Probenahme von festen Rohstoffen und Altlas- ten unter statistischen Aspekten. In: GAR-Proceedings, TU Bergakademie Freiberg 1994,
  • 5 - 12
  • J. Pilz: Robust Bayes linear prediction of regionalized variables. In: Geostatistics for the Next Century (R. Dimitrakopoulos, ed.), Kluwer, Dordrecht 1994, 464 – 475
  • H. Drygas, J. Pilz: On the equivalence of spectral theory and Bayesian analysis in minimax linear estimation. Acta Applicandae Mathematicae (1996), 1 – 15
  • J. Pilz, M.G. Schimek, G. Spöck: Taking account of uncertainty in spatial covariance estima- tion. In: Geostatistics Wollongong ’96 (E. Baafi and N. Schofield, eds.), Kluwer, Dord- recht 1997, 302 - 313
  • J. Pilz, J. Menz: Bayessche Kollokation - Äquivalenzen zwischen Ausgleichungsrechnung und Geostatistik. Das Markscheidewesen 104 (1997), Heft 3, 85 - 90
  • J. Pilz, St. Knospe: Eine Anwendung des Bayes Kriging in der Lagerstättenmodellierung. Glückauf-Forschungshefte 58 (1997) Nr. 4, 137 - 143
  • J. Pilz, V. Weber: Bayessches Kriging zur Erhöhung der Prognosegenauigkeit im Zusammen hang mit der UVP für den Bergbau (zusammen mit V. Weber). Das Markscheidewesen 105 (1998)3, 213 – 221
  • J. Pilz, R.-G. Koboltschnig: Smoothing cancer ratios in Tirol: A Bayesian model in epidemiology. In: geoenv II – Geostatistics for Environmental Applications (J. Gomez- Hernandez and A. Soares, eds.), Kluwer, Dordrecht 1999, 527 - 536
  • M. DeCort, M. Maignan, J. Pilz, R. Bruno: CIVERT - Centre for Information and Valorisa- tion of European Radioactive Contaminated Territories. Final Report, Brüssel, DGXII, 2000, 64 pp. htpp://www.ai-geostats.org
  • A. Gebhardt, R. Gismondi, J. Pilz, H. Stettner: Klassifikation von Festnetzkunden. Vienna: Telekom Austria,, Internal Report, December 2001, 12 p.
  • J. Pilz, G. Bjarnason, P. Petursson: Multivariate Analysis for Comparing Different Methods for Testing Aggregates. In: Proceedings 9th Nordic Aggregates Conference, Reykjavik, 2002, pp. 18-21.
  • J. Pilz: Bayesian Spatial Prediction Using the Matern Class of Covariance Functions. In: G. Dubois, J. Malczewski, M. de Cort (Eds.): Mapping Radioactivity in the Environment, Brüssel: Office for Official Publications of the European Communities 2003, 238 – 252
  • J. Pilz: Qualitative Merkmale junger GmbHs in Österreich. In: E. J. Schwarz, E. Grieshuber (Hrsg.): Qualitative Merkmale junger GmbHs in Österreich. Bundesministerium für Wirt- schaft und Arbeit. Wien: BMWA 2003, 152 S.
  • J. Pilz: Vom Gründungs- zum Jungunternehmen– Eine explorative Analyse. In: E. J. Schwarz, E. Grieshuber (Ed.): Vom Gründungs- zum Jungunternehmen. Springer, Wien 2003, 221 pp.
  • J. Pilz: Grundzüge der Räumlichen Statistik. In: G. Pflug (Hrsg.): ALFIS. Schulungsmateria- lien für Mitarbeiter des BMLFUW und des Lebensministeriums. Universität Wien, Institut für Statistik und Decision Support Systems, November 2003
  • V. Hofer, J. Pilz, Th. Helgason: Statistical Classification of Aggregates Using Optoelectronic Data. In: G. Bjarnason, P. Petursson (Hrsg.): Proceedings of the 10th Nordic Aggregate Re- search Conference. Tampere 2004
  • J. Pilz, P. Pluch, G. Spoeck: Bayesian Kriging with lognormal data and uncertain variogram parameters. In: Geostatistics for Environmental Applications (Renard, Ph., Demougeot- Renard, H and R. Froideveaux, Eds.); Springer, Berlin-Heidelberg 2005, 51 – 62
  • Th. Helgason, V. Hofer, J. Pilz, G Spöck Wavelet-based classification of aggregates using MIR and NIR spectra. In: Proc. 2nd Int. Workshop on Spectral Imaging, Österr. Computer- gesellschaft 194 (2005), 11 - 18
  • V. Hofer, J. Pilz, Th. Helgason: Statistical classification of different petrographic varieties of aggregates by means of near and mid-infrared spectra. Math. Geology 38 (2006), 851 - 870
  • J. Pilz, G. Spoeck: Spatial sampling design for prediction taking account of uncertain co- variance structure. Proc. Accuracy 2006 (M. Caetano, M. Painho, Eds.), Instituto Geo- gràfico Portuguès, Lisbon 2006, 109 – 118
  • V. Hofer, J. Pilz, Th. Helgason: Support vector machines for classification of aggregates by means of IR-spectra. Math. Geology 39 (2007)3, 307 – 319
  • H. Kazianka, R. Leitner, J. Pilz: Segmentation and Classification of Hyper-Spectral Skin Data. In: Data Analysis, Machine Learning and Applications (Ch. Preisach, H. Burkardt, L. Schmidt-Thieme and R. Decker, eds.), Springer Series “Studies in Classification, Data Analysis, and Knowledge Organization”, Springer, Berlin, 2008, 245 - 252
  • J. Pilz, G. Spoeck: Why do we need and how should we implement Bayesian kriging methods. Stoch. Envir. Res. And Risk Assessment 22(2008)5, 621 - 632
  • J. Pilz, H. Kazianka, G. Spöck: Interoperability – Spatial Interpolation and Automated Mapping. In: Proc. 4th International Conference on Information and Communication Tech- nologies in Bio and Earth Sciences (T. Tsiligiridis, Ed.),Athens, 2008, 110 –118
  • J. Pilz, G. Spöck: Bayesian spatial sampling design. In: Proc. 8th International Geostatistics Congress (J. M. Ortiz and X. Emery, Eds.), Gecamin Ltd., Santiago de Chile 2008, 21 – 30
  • G. Spöck, J. Pilz: Non-stationary spatial modelling using harmonic analysis. In: Proc. 8th Int. Geostatistics World Congress (J. M. Ortiz and X. Emery, Eds.), Gecamin Ltd., Santiago de Chile, 2008, 389-398
  • R. Breitenecker, J. Pilz, E. Schwarz: Presentation of Entrepreneurship Data and Aspects of Spatial Modeling. In: Interfacing Geostatistics and GIS (J. Pilz, Ed.), Springer, Berlin- Heidelberg 2009, 189 – 200
  • V. Hofer, J. Pilz, Th. Helgason: Daubechies Wavelets for Identification of Rock Variants from IR Spectra. In: Interfacing Geostatistics and GIS (J. Pilz, Ed.), Springer, Berlin- Heidelberg 2009, 79 – 88
  • G. Spöck, H. Kazianka, J. Pilz: Bayesian Trans-Gaussian Kriging with Log-Log-Transformed Skew Data. In: Interfacing Geostatistics and GIS (J. Pilz, Ed.), Springer, Berlin-Heidelberg 2009, 29 – 43
  • K. Lessiak, Ch. Kollmitzer, St. Schauer, J. Pilz, St. Rass.: Statistical Analysis of QKD Networks in Real-life Environments. In: Proc. Third Int. Conference on Quantum, Nano and Micro Technologies ICQNM 2009 (D. Avis, Ch. Kollmitzer and V. Privmann, Eds.), IEEE Computer Society, Conf. Publ. Services, Los Alamitos, CA 2009, 109 – 114
  • H. Kazianka, J. Pilz: A corrected criterion for selecting the optimum number of principal components. Austrian Journal of Statistics 38 (2009) No.3, 135-150
  • K. Lessiak, J. Pilz: Application of GLMs and GLMMs for the Analysis of QKD Networks. Proc. 8th European Young Statisticians Meeting (M. Iosifescu and V. Preda, Eds.), Univ. Bucharest 2009, 36 – 40
  • H. Kazianka, J. Pilz: Spatial Interpolation Using Copula-Based Geostatistical Models. In: geoENV VII - Geostatistics for Environmental Applications (P.M. Atkinson and C.D. Lloyd, Eds.), Series: Quantitative Geology and Geostatistics, Vol. 16, Springer, Berlin 2010, 307-319
  • G. Spöck, J. Pilz: Spatial sampling design and covariance-robust minimax prediction based on convex design ideas. Stoch. Envir. Research and Risk Assess. 24 (2010), 463 - 482
  • I. Hussain, J. Pilz, G. Spöck: Hierarchical Bayesian space-time interpolation versus spatio- temporal BME approach. Advances in Geosciences 25 (2010), 97 – 102
  • K. Lessiak, J. Pilz: Statistical Analysis of QKD Networks in Real-Life Environment. In: Ap plied Quantum Cryptography (Ch. Kollmitzer and M. Pivk, Eds.), Lecture Notes in Physics 797, Springer, Berlin-Heidelberg 2010, 123 - 149
  • H. Kazianka, J. Pilz: Copula-based geostatistical modeling of continuous and discrete data including covariates. Stoch Environ Res Risk Assess 24 (2010), 661–673 DOI 10.1007/s00477-009-0353-8
  • P. Mikosch, T. Hadrawa, K. Laubreiter, J. Brandl, J. Pilz, H. Stettner, G. Grimm: Effective- ness of respiratory-sinus-arrhythmia biofeedback on state-anxiety in patients undergoing coronary angiography. J. Advanced Nursing 66 (2010) 5, 1101 - 1110 DOI 10.1111/j.1365-2648.2010.05277.x
  • H. Nkurunziza, A. Gebhardt, J. Pilz: Bayesian modelling of the effect of climate on malaria in Burundi. Malaria Journal 9:114 (2010) http://www.malariajournal.com/content/pdf/1475-2875-9-114.pdf
  • H. Nkurunziza, A. Gebhardt, J. Pilz: Forecasting malaria cases in Bujumbura. World Acade- my of Science, Engineering and Technology 61 (2010), 253 – 258
  • H. Kazianka, J. Pilz: Geostatistical modeling using non-Gaussian copulas. Proceedings Accu- racy 2010 (N. Tate and P. Fisher, Eds.), Univ. of Leicester, p. 49-52
  • I. Hussain, G. Spöck, J. Pilz, H.-L Yu: Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan. Advances in Water Resources 33(2010), 880–886 doi:10.1016/j.advwatres.2010.04.01 M. Mohsin, J. Pilz, G. Spoeck, S. Shabaz, M.Q.Shabaz: Some distributional properties of the concomitants of record statistics for bivariate pseudo-exponential distribution and characterization. Journal of Prime Research in Mathematics 6 (2010), 32-37
  • I. Hussain, J. Pilz, G. Spoeck: Reply to Comment on “Hierarchical Bayesian space-time inter-polation versus spatio-temporal BME approach” by Kolovos (2009). Advances in Geosciences 25 (2010), 181
  • J. Pilz: Statistical Design of Experiments. In: Int. Encyclopedia of Statistical Science (M. Lovric, Ed.), Springer Science + Business Media, LLC, Heidelberg 2011, 1392-1396
  • G. Spöck, J. Pilz: Analysis of areal and spatial interaction data. In: Int. Encyclopedia of Statis-tical Science (M. Lovric, Ed.), Springer Science + Business Media, LLC, Heidelberg 2011, 35 – 39
  • H. Kazianka, J. Pilz: Model- based Geostatistics. In: Int. Encyclopedia of Statistical Science (M. Lovric, Ed.), Springer Science + Business Media, LLC, Heidelberg 2011, 833-836. Re-printed and freely available at http://statprob.com/encyclopedia/ModelBasedGeostatistics.html
  • I. Hussain, J. Pilz, G. Spöck: Homogeneous climate regions in Pakistan. Int. J. Global Warm-ing 3 (2011) 1/2, 55 - 66
  • H. Nkurunziza, J. Pilz: Impact of increased temperature on malaria transmission. Int. J. Global Warming 3 (2011) 1/2, 77 – 87
  • J. Pilz: Spatial Statistics. In: Int. Encyclopedia of Statistical Science (M. Lovric, Ed.), Springer Science + Business Media, LLC, Heidelberg 2011, 1363-1368
  • O.P. Baume, A. Gebhardt, C. Gebhardt, G.B.M. Heuvelink, J. Pilz: Network optimization algorithms and scenarios in the context of automatic mapping. Computers & Geosciences 37 (2011) 3, 289 - 294
  • H. Kazianka, J. Pilz: Bayesian spatial modeling and interpolation using copulas. Computers & Geosciences 37 (2011) 3, 310 – 319. (Best paper award for 2011)
  • E. Pebesma, D. Cornford, G. Dubois, G.B.M. Heuvelink, D. Hristopoulos, J. Pilz, U. Stöhlker, G. Morin, J.O. Skoien: INTAMAP: the design and implementation of an interoperable automated interpolation web service. Computers & Geosciences 37 (2011) 3, 343 – 352
  • H. Kazianka, M. Mulyk, J. Pilz: A Bayesian Approach to Estimating Linear Mixtures with Unknown Covariance Structure. Journal of Applied Statistics 38 (2011) 9, 1801-1817
  • D. Rasch, J. Pilz, R.L. Verdooren, A. Gebhardt: Optimal Design of Experiments with R. Chapman and Hall/ CRC Press, Boca Raton 2011
  • O. Bluder, M. Glavanovics, J. Pilz: Applying Bayesian mixture-of-expert models to statistical description of smart power semiconductor reliability. Microelectronics Reliability 51 (2011), 1464–1468
  • M. Mohsin, J. Pilz, G. Spoeck, M. Ahsanullah: A new bivariate pseudo-Gamma distribution. Journal of Applied Statistical Sciences 18 (2011) 2, 79-90
  • H. Nkurunziza, A. Gebhardt, J. Pilz: Geo-additive modeling of malaria in Burundi. Malaria Journal 2011, 10:234 doi:10.1186/1475-2875-10-234 http://www.malariajournal.com/content/10/1/234
  • D. Kurz, K. Kaspar, J. Pilz: Dynamic Maintenance in semiconductor manufacturing using Bayesian networks. Los Angeles (CA): Proc. IEEE 7th Int. Conf. on Automation Science and Engineering (CASE) (2011), 238 - 243, DOI:10.1109/CASE.2011.6042404
  • T. Svensson, T. Fulton, M. Molodovskaya, Z. Nesic, A.T. Black, L. Pickering, J. Pilz, G. Öberg : Spatial variability of VOCl fluxes from forest soil. Proc. AGU Fall Meeting (San Francisco, Dec.2011), NW, Washington, DC: American Geophys. Union (2011), B51E-0436
  • M. Mohsin, J. Pilz, G. Spoeck: On the Performance of a new bivariate pseudo Pareto distribu-tion with application to drought data. Stoch. Environ. Res. Risk Assess. 26 (2012), 925–945 , DOI 10.1007/s00477-011-0529-x
  • I. Hussain, G. Spoeck, J. Pilz, M. Faisal, Hwa-Lung Yu: Accounting for environmental co-variates in the interpolation of precipitation during monsoon periods in Pakistan. Pakistan Journal of Statistics 28 (2012) 3, 351 - 365
  • H. Kazianka, J. Pilz: Objective Bayesian Analysis of Spatial Data taking account of nugget and range parameters. The Canadian J. of Statistics 40 (2012) 2, 304 - 327
  • J. Pilz, M. Mohsin, A. Gebhardt: A bivariate pseudo Gamma distribution with application to acid rain data. Geophysical Research Abstracts Vol. 14, EGU2012-6507, 2012
  • J. Pilz, H. Kazianka, G. Spöck: Some Advances in Bayesian Spatial Prediction and Sampling Design. Spatial Statistics 1 (2012), 65-81
  • O. Bluder, J. Pilz, M. Glavanovics, K. Plankensteiner: A Bayesian Mixture Coffin-Manson Approach to Predict Semiconductor Lifetime. Proc. SMTDA2012, June 12-16, Chania, Greece (Best paper award)
  • D. Kurz, C. DeLuca, J. Pilz: Sampling decision system in semiconductor manufacturing using virtual metrology. Proc. 8th IEEE International Conference on Automation Science and Engi-neering (CASE 2012), Seoul, Korea, pp. 74 - 79 http://dx.doi.org/10.1109/CoASE.2012.6386366
  • M. Mohsin, A. Gebhardt, J. Pilz, G. Spöck: A new bivariate Gamma distribution generated from functional scale parameter with application to drought data. Stoch. Envir. Research and Risk Assess. 27 (2013) 5, 1039 - 1054, DOI 10.1007/s00477-012-0641-6
  • G. Spöck, J. Pilz: Spatial sampling design based on spectral approximations of the error pro-cess. In: J. Mateu, W. Müller (Eds.), Spatio-temporal Design: Advances in Efficient Data Ac-quisition, Wiley, New York, 2013, Ch. 4, 72 - 102
  • M. Mohsin, J. Pilz: A Recurrence Relation of Hypergeometric Series through Record Statistics and a Characterization. Journal of Applied Mathematics and Informational Sciences 7 (2013) 4, 1307-1310
  • M. Mohsin, H. Kazianka, J. Pilz: Likelihood and objective Bayesian modeling of acidity and major ions in rainfall using a bivariate pseudo Gamma distribution. Computers & Geosciences 54 (2013), 269-278 http://dx.doi.org/10.1016/j.cageo.2012.12.004
  • I. Hussain, H. Kazianka, J. Pilz, M. Faisal: Spatio-temporal modeling of particulate matter concentrations including covariates. Science International 25 (2013) 1, 15-21
  • J. Pilz: Bayesian spatial prediction using objective priors and copula-based methods. Geophysical Research Abstracts Vol. 15, EGU2013-6391, 2013
  • M. Mohsin, A. Gebhardt, J. Pilz and G. Spöck: A new bivariate Gamma distribution generated from functional scale parameter with application to drought data. Stoch. Envir. Research and Risk Assess. 27 (2013) 5, 1039 - 1054, DOI 10.1007/s00477-012-0641-6
  • L. Pickering, T. Fulton, C. Gilbert, M. Jeronimo, Z. Nesic, J. Pilz, T. Svensson and G. Öberg: Designing Portable Chambers for VOCl-Fluxes from Forest Soil - Methodological Challenges. Environmental Science & Technology 47 (2013), 14298-14305, DOI:http://dx.doi.org/10.1021/es403062c
  • K. Plankensteiner, O. Bluder and J. Pilz: Application of Bayesian Networks to predict SMART Power Semiconductor Lifetime. Proc. 9th Conf. on PhD Research in Microelelectronics and Electronics PRIME 2013,281-284 DOI:10.1109/PRIME.2013.6603175
  • D. Kurz, C. DeLuca and J. Pilz: Monitoring Virtual Metrology Reliability in a Sampling Decision System. Proc. 9th IEEE International Conf. on Automation Science and Engineering (CASE 2013), Madison, WI, pp. 20-25, http://dx.doi.org/10.1109/CASE.2013.6653949
  • J. Pilz: Some Advances in Bayesian Spatial Prediction and Sampling Design (Key Note Lecture). Abstract in: Proc. 18th EYSM, Osijek, Croatia, August 26-30, 2013
  • M. Mohsin, H. Kazianka, J. Pilz and A. Gebhardt: A New Bivariate Exponential Distribution for Modeling Moderately Negative Dependence. Statistical Methods and Applications 23 (2014) 1, 123-148
  • D. Kurz, H. Lewitschnig and J. Pilz: Bayesian Assessment of Weibull Early Life Failure Distributions. Int. J. Quality and Reliability Engineering 30 (2014) 3, 363-373
  • D. Kurz, H. Lewitschnig and J. Pilz: Decision- theoretical model for failures which are tackled by countermeasures. IEEE Transactions on Reliability 63 (2014) 2, 583 – 592 DOI:10.1109/TR.2014.2315952
  • K. Plankensteiner, O. Bluder, and J. Pilz. Bayesian Prediction of SMART Power Semicon- ductor Lifetime with Bayesian Networks. In: The Contribution of Young Researchers to Bayesian Statistics (E. Lanzarone and F. Ieva, eds.), Springer Proceedings in Mathematics & Statistics, Vol. 63, pages 109–112. Springer International Publishing, 2014 DOI:10.1007/978-3-319-02084-6_22
  • D. Kurz, H. Lewitschnig and J. Pilz: Survey of recent advanced statistical models for early life failure probability assessment in semiconductor manufacturing. Proceedings of the 2014 Winter Simulation Conference (A. Tolk, S.D. Diallo, I.O. Ryzhov, L. Yilmaz, S. Buckley, and J.A. Miller, eds.), IEEE Press Piscataway, NJ, USA ©2014, 2600-2608
  • J. Pilz, D. Kurz, S. Pampuri, A. Schirru, and C. DeLuca: A Sampling Decision System for Semiconductor Manufacturing. Relying on Virtual Metrology and Actual Measurements Proceedings of the 2014 Winter Simulation Conference (A. Tolk, S.D. Diallo, I.O. Ryzhov, L. Yilmaz, S. Buckley, and J.A.Miller, eds.), IEEE Press Piscataway, NJ, USA ©2014, 2649-2660
  • F. Khan and J. Pilz: Climate Change and its Impacts on Water Resources and Management of Tarbela Reservoir under IPCC Climate Change Scenarios in Upper Indus Basin, Pakistan. Geophysical Research Abstracts Vol. 15, EGU2014-2285, 2014
  • K. Plankensteiner, O. Bluder and J. Pilz: Modeling and prediction of smart power semiconductor lifetime data using a Gaussian process prior. Proceedings of the 2014 Winter Simulation Conference (A. Tolk, S. D. Diallo, I. O. Ryzhov, L. Yilmaz, S. Buckley, and J. A. Miller, eds.), IEEE Press Piscataway, NJ, USA ©2014, 2671-2681
  • A.Zernig, O. Bluder, J. Pilz and A. Kästner: Device level maverick screening detection of risk devices through independent component analysis. Proc. 2014 Winter Simulation Conference (A. Tolk, S.D. Diallo, I.O. Ryzhov, L. Yilmaz, S. Buckley, and J.A. Miller, eds.), IEEE Press Piscataway, NJ, USA ©2014, 2661-2670M
  • S. König, H. Kazianka, J. Pilz and J. Temme: Estimation of non-strict Archimedean copulas and its application to quantum networks. Applied Stochastic Models in Business and Industry (Wiley). 31 (2015) 4, 464-482
  • K. Plankensteiner, O. Bluder and J. Pilz: Bayesian Network Model with Application to Smart Power Semiconductor Lifetime Data. J. Risk Analysis 35 (2015) 9, 1623-1639
  • F. Khan, J. Pilz, David A. Wiberg and M. Amjad: Climate Variability and its Impacts on Water Resources in Upper Indus Basin under IPCC Climate Change Scenarios. Int. J. Global Warming 8 (2015) 1, 46-69
  • D. Kurz, C. DeLuca and J. Pilz: A Sampling Decision System for Virtual Metrology in Semiconductor Manufacturing. IEEE Transactions on Automation Science and Engineering 12 (2015)1, 75-83
  • D. Kurz, H. Lewitschnig and J. Pilz: Failure Probability Estimation For Differently Sized Products in Semiconductor Manufacturing. Applied Stochastic Models in Business and Industry 31 (2015) 5, 732-744
  • D. Kurz, H. Lewitschnig and J. Pilz: An advanced area scaling approach for semiconductor burn-in. Microelectronics Reliability 55(2015)1, 129-137, DOI: 10.1016/ j.microrel.2014. 09.007
  • G. Spoeck and J. Pilz: Simplifying objective functions and avoiding stochastic search algorithms in spatial sampling design. Front. Environ. Sci. 3:39 (2015), 1-22
  • F. Khan, J. Pilz and J. Winkler: Climate Change and its Impacts on Water Resources and Management of Tarbela Reservoir under IPCC Climate Change Scenarios in the Upper Indus Basin, Pakistan. European Geosciences Union General Assembly, EGU2015, Vienna
  • N. Vollert, J. Schicker, Ch. Hirschl, M. Kraft and J. Pilz: Designing Efficient Computer Experiments - The Step Beyond Finite Element Modelling. 16th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE 2015), IEEE Xplore Digital Library; 04/2015. 6 p.
  • A. Zernig, O. Bluder, J. Pilz, A. Kästner and A. Krauth: Identification of risk devices using Independent Component Analysis for semiconductor measurement data. Proc. 2015 Int. Symposium on Semiconductor Manufacturing Intelligence (ISMI2015)
  • H. Lewitschnig, D. Kurz and J. Pilz: New Models for Burn-In of Semiconductor Devices. Proc. 2015 Int. Symposium on Semiconductor Manufacturing Intelligence (ISMI2015)
  • M. Mohsin, J. Pilz and A. Gebhardt: An explicit distribution to model the proportion of heating and cooling degree days. Communications in Statistics - Simulation and Computation vol. 45, issue 7 (2016). DOI: 10.1080/03610918.2014.915037
  • U. Haque, P. Blum, J. Pilz et al.: Fatal Landslides in Europe. Landslides (2016) 13: 1545, DOI 10.1007/s10346-016-0689-3
  • N. Vollert, M. Ortner and J. Pilz: Construction of Smooth Borders for Treed Gaussian Process Models. Proc. 4th Int. Conference on the Interface between Statistics and Engineering (ICISE) 2016, submitted to: Int. J. Industrial Engineering: Theory, Practice and Applications
  • A. Zernig, O. Bluder, J. Pilz, A. Kästner an A. Krauth: Identification of Risk Devices Using Independent Component Analysis for Semiconductor Measurement Data. The International Journal of Industrial Engineering: Theory, Applications and Practice 23(2016)5 http://journals.sfu.ca/ijietap/index.php/ijie/article/view/2852
  • F. Khan, J. Pilz and S. Ali: Improved Hydrological Projections and Reservoir Management in the Upper Indus Basin under Changing Climate. Water and Environment Journal 31(2017) 2, 235-244
  • B. Zhao, L. Han, J. Pilz, J. Wu, F. Khan and D. Zhang: Metallogenic efficiency from deposit to region–A case study in western Zhejiang Province, southeastern China, Ore Geol. Reviews, Volume 86 (2017), 957-970. http://dx.doi.org/10.1016/j.oregeorev.2016.10.003
  • D. Kurz, H. Lewitschnig and J. Pilz: Modeling of chip synergies for failure probability estimation in semiconductor manufacturing. J. Applied Statistics 44 (2017) 6, 955-967 DOI: 10.1080/02664763.2016.1189522
  • S. Riazy, T. Wendler, J. Pilz, M. Glos and T. Penzel: Automatic Two-Channel Sleep-Staging Using A Predictor-Corrector Method. Proc. 8th Int. Workshop on Biosignal Interpretation, Osaka University, 2017 http://www.p.u-tokyo.ac.jp/~bsi2016/PDF/BSI2016_proceedings.pdf
  • G. García-Santos, M. Pleschberger, M. Scheiber, M. and J. Pilz: How to predict pesticide drift from hand-held knapsack sprayers on soils. 72. Arbeitsgemeinschaft für Lebensmittel-, Veterinär- und Agrarwesen (ALVA) Tagung, Waldkirche am See 2017, pages 361-363. ISSN 1606-612X.
  • S. Riazy, T. Wendler, J. Pilz, M. Glos and T. Penzel: Heuristic Approximation of the MAP Estimator for Automatic Two-channel Sleep Staging. Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017), Porto, Scitepress 2017, Volume 4: BIOSIGNALS, pages 236-241, ISBN: 978-989-758-212-7
  • F. Khan and J. Pilz: A Bayesian Approach for GCMs Selection and Ensemble Projections under the latest Emission Scenario EGU 2017-5259, Geophysical Research Abstracts, Copernicus Publications, Göttingen, April 2017, Vol 19, S. 5259 http://meetingorganizer.copernicus.org/EGU2017/EGU2017-5259.pdf
  • G. Garcia-Santos, M. Pleschberger, M. Scheiber and J. Pilz: Spatial interpolation of pesticide drift from hand-held knapsack sprayers used in potato production.EGU 2017-13729, Geophysical Research Abstracts, Copernicus Publications, Göttingen, April 2017, Vol 19, S. 13729 http://meetingorganizer.copernicus.org/EGU2017/EGU2017-13729.pdf
  • S. Schrunner, O. Bluder and J. Pilz: Optimal Experimental Design for Semiconductor Lifetime Mission Profile Testing. Journal of Multidisciplinary Engineering Science Studies (JMESS) 3 (2017) 2, 1440-1446 http://jmess.org/index.php/vol-3-issue-2-february-2017/
  • D. Rasch and J. Pilz: Optimal Design of Surveys and Experiments. Psychol. Test and Assessment Modeling, 59 (2017), 359 – 371
  • M. Ortner, Ch. Huber, N. Vollert, J. Pilz and D. Süss: Application of 3D-printed magnets for magnetic position detection systems. Proc. IEEE Sensors 2017, Glasgow. DOI:10.1109/ICSENS.2017.8233930
  • N. Vollert, M. Ortner and J. Pilz: Benefits and Application of Tree Structures in Gaussian Process Models to Optimize Magnetic Field Shaping Problems. In: Statistics and Simulation (J. Pilz, D. Rasch, K. Moder and V. Melas, Eds., Proc. 8th Int. Workshop on Simulation), Springer, Berlin, Heidelberg 2018, pp. 161 – 170
  • D. Kurz, H. Lewitschnig and J. Pilz: An overview on recent advances in statistical burn-in modeling for semiconductor devices.To appear in: Statistics and Simulation (J. Pilz, D. Rasch, K. Moder and V. Melas, Eds., Proc. 8th Int. Workshop on Simulation), Springer, Berlin, Heidelberg 2018, pp. 371 - 380
  • Riazy, S., Wendler, T., Pilz, J., Glos, M. and T. Penzel: Automatic two-channel sleep- staging using a predictor-corrector method. Physiological Measurement 39(2018)1: 014006. Online: doi.org/10.1088/1361-6579/aaa109.
  • F. Khan and J. Pilz: Modelling and Sensitivity Analysis of River Flow in the Upper Indus Basin, Pakistan. Int. Journal of Water 12 (2018) 1, 1-21 DOI: 10.1504/IJW.2018.10011173
  • Han, L., Zhao, B., Wu, J., Zhang, S.-J., Pilz, J. and F. Yang: An integrated approach for ex- traction of lithology information using the SPOT 6 imagery in a heavily Quaternary covered region –North Baoji District of China. Geological Journal, 53 (2018) S1, 352-363. Online: doi.org/10.1002/gj.3061.
  • N. Vollert, M. Ortner and J. Pilz: Benefits and Application of Tree Structures in Gaussian Process Models to Optimize Magnetic Field Shaping Problems. In: Statistics and Simulation (J. Pilz, D. Rasch, K. Moder and V. Melas, Eds., Proc. 8th Int. Workshop on Simulation 2015), Springer, Berlin, Heidelberg 2018, p. 161 - 170
  • Khan, F., Ali, S. and J. Pilz: Evaluation of statistical downscaling models by using pattern and dependent structure in the monsoon dominated region of Pakistan. Weather 73 (2018) 6, 193 – 203. Online: http://onlinelibrary.wiley.com/doi/10.1002/wea.3164/abstract
  • D. Kurz, H. Lewitschnig and J. Pilz: An overview on recent advances in statistical burn-in modeling for semiconductor devices. In: Statistics and Simulation (J. Pilz, D. Rasch, K. Moder and V. Melas, Eds., Proc. 8th Int. Workshop on Simulation 2015), Springer, Berlin, Heidelberg 2018, p. 371 – 380
  • Ran Wang, Jingyiu Lin, Bo Zhao, Lu Li, Zhouxuan Xiao and J. Pilz: Integrated Approach for Lithological Classification Using ASTER Imagery in a Shallowly Covered Region—The Eastern Yanshan Mountain of China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11(2018)12, 4791-4807
  • D. Alagić, O, Bluder and J. Pilz: Quantification and Prediction of Damage in SAM Images of Semiconductor Devices. In: Campilho A., Karray F., ter Haar Romeny B. (eds) Image Analysis and Recognition. ICIAR 2018. Lecture Notes in Computer Science, vol 10882, Springer, Cham, p. 490-496
  • N. Vollert, M. Ortner and J. Pilz. Robust additive Gaussian process models using reference priors and cut-off-designs. Applied Mathematical Modelling 65 (2019), 586 – 596
  • Zhao, B., Wu, J., Yang, F., Pilz, J. and D. Zhang: A novel approach for extraction of the Gaoshanhe-Group outcrops using Landsat Operational Land Imager (OLI) data in the heavily loess-covered Baoji District, Western China. Ore Geology Reviews 108 (2019), 88 - 100. Online: doi.org/10.1016/j.oregeorev.2018.01.034.
  • S. Schrunner, O. Bluder, A. Zernig and J. Pilz. How to predict the lifetime of semiconductors in real-world applications with limited test resources? In: Quality Management in Technology 2019 (J. Wittmann and J. Bergholz, Eds.), Amazon Media EU, Luxembourg 2019, p. 53-90
  • Bo Zhao, Fan Yang, Rongzhen Zhang, Junping Shen, J. Pilz and Dehui Zhang: Application of Unsupervised Learning of Finite Mixture Models in ASTER VNIR Data-Driven Land Use Classification. Journal of Spatial Science (2019), DOI: 10.1080/14498596.2019.1570478
  • F. Khan and J. Pilz.: Statistical methodology for evaluating process-based climate models. In: Climate Change and Global Warming (A. Amini, Ed.), IntechOpen, London, 2019, p. 43 – 61, DOI: 10.5772/intechopen.80984
  • W. Shabbir and J. Pilz: Bayesian Spatio-temporal Analysis for Dengue Fever in Major Cities of Pakistan (2006-2017). Conf. Proceedings of 12th RSEP Int. Social Sciences Conference (M. Veysel and P. Chodnicka-Jaworska, eds.), Barcelona 2019, p. 1 – 9, ISBN: 978-605-80676-0-8, E-ISSN: 2547-9385
  • D. Alagic, O. Pfeiler and J. Pilz: Unsupervised Algorithm to Detect Damage Patterns in Microstructure Images of Metal Films. Proc. 3rd IEEE Int. Conf. On Image Processing, Applications and Systems (IPAS 2018), Sophia Antipolis, IEEE Xplore Digital Library; 2019. 6 p.
  • U. Haque, P. da Silva, G. Davoli, J. Pilz et al.: The human cost of global warming: Deadly landslides and their triggers (1995–2014), Science of the Total Environment 682 (2019), 673 -684. https://doi.org/10.1016/j.scitotenv.2019.03.415
  • K. Posch, M. Arbeiter and J. Pilz. A novel Bayesian approach for variable selection in linear regression models. Computational Statistics and Data Analysis 144 (2020) https://doi.org/10.1016/j.csda.2019.106881
  • F. Khan and J. Pilz: A novel Approach for Modelling Pattern and Spatial Dependence Structures between Climate Variables by Combining Mixture Models with Copula Models. Int J Climatol. 40 (2020), 1049–1066. https://doi.org/10. 1002/joc.6255
  • M. Pleschberger, S. Schrunner and J. Pilz: An Explicit Solution for Image Restoration using Markov Random Fields. J Sign Process Syst 92 (2020), 257–267 https://doi.org/10.1007/s11265-019-01470-9
  • D. Rasch, L.R. Verdooren and J. Pilz: Applied Statistics - Theory and Problem Solutions with R. J. Wiley, Oxford 2020
  • B. Rainer, J. Pilz and M. Deutschmann: Assessing the Statistical Quality of RNGs. In: Kollmitzer C., Schauer S., Rass S., Rainer B. (eds) Quantum Random Number Generation. Quantum Science and Technology. Springer 2020, Cham, pp. 45-64
  • Ch. Petschnigg and J. Pilz: I Uncertainty aware deep point based neural network for 3D object classification. To appear in: Proc. Int. Data Science Conf. (IDSC) Dornbirn 2020, 8 p.
  • G. Garcia-Santos, M. Scheiber and J. Pilz: Spatial interpolation methods to predict drift deposits on soil after spray of pesticides. Chemosphere 258(2020), 127231 https://doi.org/10.1016/j.chemosphere.2020.127231
  • D. Rasch, J. Pilz, P. Schneider and R.L. Verdooren: An Empirical Approach That a Two-Stage Procedure is Better Than Bechhofer’s Approach. J Stat Theory Pract 14, 54 (2020). https://doi.org/10.1007/s42519-020-00098-4
  • S. Abbas, M. Mohsin and J. Pilz: A new life time distribution with applications in relability and environmental sciences. Journal of Statistics and Management Systems 2020, DOI: 10.1080/09720510.2019.1700890
  • P. Plum, H. Lewitschnig, and J. Pilz: Exact Confidence Intervals for the Hazard Rate of a Series Reliability System. 2020 Annual Reliability and Maintainability Symposium (RAMS), IEEE Xplore, https://doi.org/10.1109/RAMS48030.2020.9153656
  • J. Steinbrener, K. Posch and J. Pilz: Measuring the Uncertainty of Predictions in Deep Neural Networks with Variational Inference. Sensors 2020, 20, 6011, doi:10.3390/s20216019
  • C. Petschnigg, S. Bartscher and J. Pilz, "Point Based Deep Learning to Automate Automotive Assembly Simulation Model Generation with Respect to the Digital Factory," 2020 9th International Conference on Industrial Technology and Management (ICITM), Oxford, United Kingdom, 2020, pp. 96-101, doi: 10.1109/ICITM48982.2020.9080347.
  • W. Shabbir, J. Pilz and A. Naeem: A Spatial-Temporal Study for Spread of Dengue Depending on Climate Factors in Pakistan (2006-2017). BMC Public Health (2020) 20:995 https://doi.org/10.1186/s12889-020-08846-8
  • K. Posch and J. Pilz: Correlated Parameters to Accurately Measure Uncertainty in Deep Neural Networks. IEEE Transactions on Neural Networks and Learning Systems 32(2021) 3, 1037-1051 https://doi.org/10.1109/TNNLS.2020.2980004
  • F. Khan, J. Pilz and A. Shaukat: Evaluation of CMIP5 Models and Ensemble Climate Projections using a Bayesian Approach: A Case Study of the Upper Indus Basin, Pakistan. Environmental and Ecological Statistics 2021 https://doi.org/10.1007/s10651-021-00490-8
  • Ch. Petschnigg and J. Pilz: Uncertainty Estimation in Deep Neural Networks for Point Cloud Segmentation in Factory Planning. Modelling 2021, 2, 1–17. https://doi.org/10.3390/modelling2010001
  • Ch. Petschnigg, M. Spitzner, L. Weitzendorf and J. Pilz: From a Point Cloud to a Simulation Model - Bayesian Segmentation and Entropy Based Uncertainty Estimation for 3D Mod- elling. Entropy 2021, 23, 301. https://doi.org/10.3390/e23030301
  • M. Mohsin and J. Pilz: Stochastic model for drought analysis of the Colorado River Basin. Stoch. Envir. Res. Risk Assess. 2021. https://doi.org/10.1007/s00477-021-01989-z
  • G. Fenk-Oczlon and J. Pilz: Linguistic Complexity: Relationships Between Phoneme Inventory Size, Syllable Complexity, Word and Clause Length, and Population Size. Front. Commun. 6:626032, doi: 10.3389/fcomm.2021.626032
  • D. Kurz, H. Lewitschnig and J. Pilz: Flexible time reduction method for burn‐in of high‐ quality products. Quality and Reliability Engineering International 2021. https://doi.org/10.1002/qre.2896
  • K. Posch, C. Truden, P. Hungerländer and J. Pilz: A Bayesian approach for predicting food and beverage sales in staff canteens and restaurants. Int. Journal of Forecasting 2021, https://doi.org/10.1016/j.ijforecast.2021.06.001