Publications

In God we trust. All others must bring data. (W. E. Deming)

Peer-reviewed Journals

2024

  • Otto, P., Dogan, O., Taspinar, S., Schmid, W., Bera, A. K. (2024): Spatial and Spatiotemporal Volatility Models: A Review. Journal of Economic Surveys (DOI)
  • Otto, P. (2024): A multivariate spatial and spatiotemporal ARCH model. Spatial Statistics 60 (DOI)
  • Malinovskaya, A., Mozharovskyi, P., Otto, P. (2024): Statistical process monitoring of artificial neural networks. Technometrics 66(1) (DOI, R/Python-Code)
  • Mattera, R., Otto, P. (2024): Network log-ARCH models for forecasting stock market volatility. International Journal of Forecasting (DOI, R-Code)
  • Otto, P., Dogan, O., Taspinar, S. (2024): Dynamic Spatiotemporal ARCH Models. Spatial Economic Analysis 19(2) (DOI, R-Code)
  • Otto, P., Alessandro Fusta Moro, Jacopo Rodeschini, Qendrim Shaboviq, Rosaria Ignaccolo, Natalia Golini, Michela Cameletti, Paolo Maranzano, Francesco Finazzi, Alessandro Fassò (2024): Spatiotemporal modelling of PM2.5 concentrations in Lombardy (Italy) -- A comparative study. Environmental and Ecological Statistics (DOI)
  • Dorau, K., Rückamp, D., Weber, C., Scheeder, G., Reßing, R., Peth, S., Otto, P., Altmann, K., Fries, E., Hoppe, M. (2024): Characterization and spatial distribution of mesoplastics in an arable soil. European Journal of Soil Science (DOI)
  • Belbe, S., Moldovan, D., Andries, A., Otto, P., Mare, C. (2024): Evaluation of the space-time effects of Covid-19 on household loans and savings in Romania - A spatial panel data approach at county level. Emerging Markets Review (DOI)
  • Tzung, H. K., Pathmanathan, D., Otto, P., Dabo-Niang, S. (2024): A Markov-switching spatio-temporal ARCH model. Stat (DOI)
  • Mohammadi, R., Taleai, M., Otto, P., Sester, M. (2024): Analyzing urban crash incidents: an advanced endogenous approach using spatiotemporal weights matrix. Transactions in GIS 28(2) (DOI)
  • Bahlau, S., Butenhof, F., Schumacher, R., Kelm, A., Meins-Becker, A., Indorf, K., Steinmann, R., Linhard, K., Otto, P., Nasiriboroujeni, M. (2024): BIM-Effizienz: Innovatives Kostenmanagement auf Basis objektorientierter Bauwerksmodelle. BBSR-Online-Publikation 10/2024, Bonn (html)

2023

  • Otto, P., Dogan, O., Taspinar, S. (2023): A Dynamic Spatiotemporal Stochastic Volatility Model with an Application to Environmental Risks. Econometrics and Statistics (DOI, MATLAB-Code)
  • Fülle, M., Otto, P. (2023): Spatial GARCH Models for Unknown Spatial Locations – An Application to Financial Stock Returns. Spatial Economic Analysis (DOI, R-Code)
  • Otto, P., Steinert, R. (2023): Estimation of the Spatial Weighting Matrix for Spatiotemporal Data under the Presence of Structural Breaks. Journal of Computational and Graphical Statistics, 32:2, 696-711 (DOI, R-Code)
  • Maranzano, P., Otto, P., Fassò, A. (2023): Adaptive LASSO estimation for functional hidden dynamic geostatistical models. Stochastic Environmental Research and Risk Assessment (DOI)
  • Fassò, A., Rodeschini, J., Fusta Moro, A., Shaboviq, Q., Maranzano, P., Cameletti, M., Finazzi, F., Golini, N., Ignaccolo, R., Otto, P. (2023): Agrimonia: a dataset on livestock, meteorology and air quality in the Lombardy region, Italy. nature Scientific Data 10(143) (DOI, Zenodo dataset)
  • Otto, P., Otto, P. (2023): What's in a name? Significance 20(1) (DOI)
  • Harke, F. H., Otto, P. (2023): Solar Self-Sufficient Households as a Driving Factor for Sustainability Transformation. Sustainability 15(3) (DOI)

2022

  • Otto, P., Schmid, W. (2022): A general framework for spatial GARCH models. Statistical Papers (DOI)
  • Piter, A., Otto, P., Alkhatib, H. (2022): The Helsinki Bike-Sharing Systems - Insights gained from a spatiotemporal functional model. Journal of the Royal Statistical Society Series A (DOI)
  • Harke, F. H., Merk, M., Otto, P. (2022): Estimation of Asymmetric Spatial Autoregressive Dependence on Irregular Lattices. Symmetry 14(7) (DOI)
  • Merk, M., Otto, P. (2022): Estimation of the spatial weighting matrix for regular lattice data -- An adaptive lasso approach with cross-sectional resampling. Environmetrics 33(1) (DOI)

2021

  • Otto, P., Piter, A., Gijsman, R. (2021): Statistical Analysis of Beach Profile Evolution and External Influences: Applying a Spatiotemporal Functional Approach. Coastal Engineering 170 (DOI)
  • Fassò, A., Maranzano, P., Otto, P. (2021): Spatiotemporal variable selection and air quality impact assessment of COVID-19 lockdown. Spatial Statistics (online first) (DOI)
  • Otto, P., Schmid, W., Garthoff, R. (2021): Stochastic Properties of Spatial and Spatiotemporal ARCH Models. Statistical Papers 62 (DOI)
  • Merk, M., Otto, P. (2021): Directional spatial autoregressive dependence in the conditional first- and second-order moments. Spatial Statistics 41 (DOI)
  • Malinovskaya, A., Otto, P. (2021): Online network monitoring. Statistical Methods & Applications, Special Issue on Network Modelling 30 (DOI)

2020

  • Merk, M., Otto, P. (2020): Estimation of Anisotropic, Time‐Varying Spatial Spillovers of Fine Particulate Matter Due to Wind Direction. Geographical Analysis 52(2) (DOI)
  • Otto, P., Otto, P. (2020): Impact of academic authorship characteristics on article citations. REVSTAT (online first) (DOI)
  • Garthoff, R., Otto, P. (2020): Spatiotemporal procedures for the statistical surveillance of spatial autoregressive models with heavy tails. Communications in Statistics - Simulation and Computation

2019

  • Otto, P. (2019): spGARCH: An R-Package for Spatial ARCH and GARCH Models. The R Journal 11(2) (DOI, CRAN)

2018

  • Otto, P., Schmid, W., Garthoff, R. (2018): Generalised Spatial and Spatiotemporal Autoregressive Conditional Heteroscedasticity. Spatial Statistics 26 (DOI)
  • Otto, P., Schmid, W. (2018): Spatiotemporal Analysis of German Real Estate Prices. The Annals of Regional Science 60(1) (DOI)
  • Otto, P., Schmid, W. (2018): Discussion of "Statistical methods for network surveillance" by Daniel Jeske, Nathaniel Stevens, Alexander Tartakovsky, and James Wilson. Applied Stochastic Models in Business and Industry 34(4) (DOI)
  • Garthoff, R., Otto, P. (2018): Verfahren zur Überwachung räumlicher autoregressiver Prozesse mit externen Regressoren. AStA Wirtschafts- und Sozialstatistisches Archiv (DOI)
  • Garthoff, R., Otto, P. (2018): Control charts for multivariate spatial autoregressive models. AStA - Advances in Statistical Analysis 101(1) (DOI)

2017

  • Otto, P. (2017): A Note on Efficient Simulation of Multidimensional Spatial Autoregressive Processes. Communications in Statistics - Simulation and Computation 46(6) (DOI)

2016

  • Otto, P., Schmid, W. (2016): Detection of Spatial Change Points in the Mean and Covariances of Multivariate Simultaneous Autoregressive Models. Biometrical Journal 58(5) (DOI)
  • Lange, A.-L., Otto, P. (2016): Bayes'sche Statistik in der Dienstleistungsforschung. AStA Wirtschafts- und Sozialstatistisches Archiv 10(4) (DOI)

Peer-reviewed Book Chapters and Conference Proceedings

  • Otto, P., Sibbertsen, P. (2024): Spatial autoregressive fractionally integrated moving average model. Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science. Springer (DOI)
  • Maranzano, P., McConville, K., Otto, P., Carillo, F. (2023): A geostatistical investigation of the ammonia-livestock relationship in the Po Valley, Italy. Annual Meeting of the Italian Statistical Society 2023
  • Otto, P. (2021): Parallelized Monitoring of Dependent Spatiotemporal Processes. In: Knoth S., Schmid W. (eds) Frontiers in Statistical Quality Control 13. ISQC 2019. Frontiers in Statistical Quality Control. Springer, Cham (DOI)
  • Malinovskaya A., Otto, P., Peters, T. (2021): Statistical learning for change point and anomaly detection in graphs. arXiv:2011.06080 (accepted: Springer Handbook on Artificial Intelligence, Big Data, Data Science and Machine Learning in Statistics)
  • Otto, P. (2019): Modeling Spatial Dependence in Local Risks and Uncertainties. Proceedings of the 29th European Safety and Reliability Conference. pp. 2685-2692. (Link)
  • Antoniuk, A., Merk, M., Otto, P. (2019): Spatial Statistics, or how to extract knowledge from data. n: Werner M., Chiang YY. (eds) Handbook of Big Geospatial Data. Springer Handbook Series in Computer Science, Cham (DOI)
  • Gijsman, R., Otto, P., Schlurmann, T., Visscher, J. (2019): Statistical Analysis of Sylt's Coastal Profiles using a Spatiotemporal Functional Model. Smart Statistics for Smart Applications, Pearson Proceedings (DOI)
  • Garthoff, R., Otto, P. (2015): Simultaneous surveillance of means and covariances of spatial models. In: Steland A., Rafajłowicz E., Szajowski K. (eds) Stochastic Models, Statistics and Their Applications. Springer Proceedings in Mathematics & Statistics, vol 122. Springer, Cham. (DOI)
  • Otto, P. (2010): Evaluation of Innovative Potential. Saint Petersburg State University (Russia), 16th International Conference in Economics for Young Researchers "Companies and Reforms in Russia" (in Russian language)

Statistical Software

  • Otto, P.: R-Package spGARCH. A collection of functions to deal with spatial and spatiotemporal autoregressive conditional heteroscedasticity (spatial ARCH and GARCH models) (CRAN)

Open Data

  • Fassò, A., Rodeschini, J., Fusta Moro, A., Shaboviq, Q., Maranzano, P., Cameletti, M., Finazzi, F., Golini, N., Ignaccolo, R., Otto, P. (2022): AgrImOnIA: Open Access dataset correlating livestock and air quality in the Lombardy region, Italy. Zenodo (DOI)

Edited books

  • Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science -- Essays in Honour of Wolfgang Schmid. Knoth, S., Okhrin, Y., Otto, P. (eds), Springer Heidelberg (DOI)

Textbooks

  • Otto, P., Lange, A.-L. (2017): Arbeitsbuch der Angewandten Statistik - Mit Aufgaben zur Software R und detaillierten Lösungen. Springer & Gabler, Heidelberg (Springer Link)

My arXiv articles

Below are my 4 most recent publications on arXiv, a full list can be found here: https://arxiv.org/a/0000-0002-9796-6682.html

Spatial ARCH Model (SpaSta)

Inspired by the time-series ARCH model developed by Robert F. Engle (1982), for which he was awarded the Nobel Prize, we have introduced a univariate spatial ARCH model in 2016 (first published arXiv paper).

Research Interest Score is higher than 93% of all articles published in 2018 (Researchgate)

Agrimonia Dataset (nature Scientific Data)

Dataset published: daily air quality, weather, and agricultural/livestock activity data for Lombardy, Italy to aid air quality research.

Research Interest Score is higher than 94% of all articles published in 2023 (Researchgate)

Estimation of the Spatial Weights Matrix (JCGS)

We propose an adaptive LASSO estimation procedure to fully recover the unknown weight matrix of spatial autoregressive panels with locally varying mean levels.

Research Interest Score is higher than 92% of all articles published in 2022 (Researchgate)

Statistical Analysis of Coastal Profiles (CoastEng)

Fully data-driven statistical model to understand the spatial and temporal evolution of coastal profiles (e.g. for efficient intervention designs against coastal erosion).

Research Interest Score is higher than 89% of all articles published in 2021 (Researchgate)