2025

Colombo, P., Mattera, R. and Otto, P. (2025) Simple yet effective: a comparative study of statistical models for yearly hurricane forecasting. Environmetrics, 36(3), e70009. (doi: 10.1002/env.70009)

Otto, P. (2025) Discussion on “Assessing predictability of environmental time series with statistical and machine learning models” by Bonas et al. Environmetrics, 36(2), e2898. (doi: 10.1002/env.2898)

2024

Belbe, Ș., Moldovan, D., Andrieș, A. M., Otto, P. and 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, 63, 101209. (doi: 10.1016/j.ememar.2024.101209)

Dorau, K., Rückamp, D., Weber, C., Scheeder, G., Reßing, R., Peth, S., Otto, P. , Altmann, K., Fries, E. and Hoppe, M. (2024) Characterization and spatial distribution of mesoplastics in an arable soil. European Journal of Soil Science, 75(6), e70016. (doi: 10.1111/ejss.70016)

Otto, P. , Fasso, A. and Maranzano, P. (2024) A review of regularised estimation methods and cross-validation in spatiotemporal statistics. Statistics Surveys, (Accepted for Publication)

Knoth, S., Okhrin, Y. and Otto, P. (Eds.) (2024) Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science: Essays in Honour of Wolfgang Schmid. Springer: Cham. ISBN 9783031691102 (In Press)

Mattera, R. and Otto, P. (2024) Network log-ARCH models for forecasting stock market volatility. International Journal of Forecasting, 40(4), pp. 1539-1555. (doi: 10.1016/j.ijforecast.2024.01.002)

Khoo, T. H., Pathmanathan, D., Otto, P. and Dabo‐Niang, S. (2024) A Markov‐switching spatio‐temporal ARCH model. Stat, 13(3), e713. (doi: 10.1002/sta4.713)

Otto, P. , Doğan, O., Taspinar, S., Schmid, W. and Bera, A. (2024) Spatial and spatiotemporal volatility models: a review. Journal of Economic Surveys, (doi: 10.1111/joes.12643) (Early Online Publication)

Otto, P. (2024) A multivariate spatial and spatiotemporal ARCH model. Spatial Statistics, 60, 100823. (doi: 10.1016/j.spasta.2024.100823)

Mohammadi, R., Taleai, M., Otto, P. and Sester, M. (2024) Analyzing urban crash incidents: an advanced endogenous approach using spatiotemporal weights matrix. Transactions in GIS, 28(2), pp. 368-410. (doi: 10.1111/tgis.13138)

Otto, P. , Doğan, O. and Taşpınar, S. (2024) Dynamic spatiotemporal ARCH models. Spatial Economic Analysis, 19(2), pp. 250-271. (doi: 10.1080/17421772.2023.2254817)

Otto, P. , Fusta Moro, A., Rodeschini, J., Shaboviq, Q., Ignaccolo, R., Golini, N., Cameletti, M., Maranzano, P., Finazzi, F. and Fassò, A. (2024) Spatiotemporal modelling of PM2.5 concentrations in Lombardy (Italy): a comparative study. Environmental and Ecological Statistics, (doi: 10.1007/s10651-023-00589-0) (Early Online Publication)

Malinovskaya, A., Mozharovskyi, P. and Otto, P. (2024) Statistical process monitoring of artificial neural networks. Technometrics, 66(1), pp. 104-117. (doi: 10.1080/00401706.2023.2239886)

Fülle, M. J. and Otto, P. (2024) Spatial GARCH models for unknown spatial locations – an application to financial stock returns. Spatial Economic Analysis, 19(1), pp. 92-105. (doi: 10.1080/17421772.2023.2237067)

2023

Otto, P. , Doğan, O. and Taşpınar, S. (2023) A dynamic spatiotemporal stochastic volatility model with an application to environmental risks. Econometrics and Statistics, (doi: 10.1016/j.ecosta.2023.11.002) (In Press)

Otto, P. and 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), pp. 696-711. (doi: 10.1080/10618600.2022.2107530)

Fassò, A., Rodeschini, J., Fusta Moro, A., Shaboviq, Q., Maranzano, P., Cameletti, M., Finazzi, F., Golini, N., Ignaccolo, R. and Otto, P. (2023) Agrimonia: a dataset on livestock, meteorology and air quality in the Lombardy region, Italy. Scientific Data, 10(1), 143. (doi: 10.1038/s41597-023-02034-0) (PMID:36934159) (PMCID:PMC10024000)

Harke, F. and Otto, P. (2023) Solar self-sufficient households as a driving factor for sustainability transformation. Sustainability, 15(3), 2734. (doi: 10.3390/su15032734)

Otto, P. and Otto, P. (2023) What’s in a name? Significance, 20(1), pp. 34-37. (doi: 10.1093/jrssig/qmad010)

2022

Garthoff, R. and Otto, P. (2022) Spatiotemporal procedures for the statistical surveillance of spatial autoregressive models with heavy tails. Communications in Statistics: Simulation and Computation, 51(10), pp. 5709-5737. (doi: 10.1080/03610918.2020.1779294)

Otto, P. and Schmid, W. (2022) A general framework for spatial GARCH models. Statistical Papers, (doi: 10.1007/s00362-022-01357-1) (Early Online Publication)

Otto, P. and Otto, P. (2022) Impact of academic authorship characteristics on article citations. Revstat Statistical Journal, 20(4), pp. 427-447. (doi: 10.57805/revstat.v20i4.382)

Harke, F. H., Merk, M. S. and Otto, P. (2022) Estimation of Asymmetric Spatial Autoregressive Dependence on Irregular Lattices. Symmetry, 14(7), 1474. (doi: 10.3390/sym14071474)

Piter, A., Otto, P. and Alkhatib, H. (2022) The Helsinki bike‐sharing system—Insights gained from a spatiotemporal functional model. Journal of the Royal Statistical Society: Series A (Statistics in Society), 185(3), pp. 1294-1318. (doi: 10.1111/rssa.12834)

Fassò, A., Maranzano, P. and Otto, P. (2022) Spatiotemporal variable selection and air quality impact assessment of COVID-19 lockdown. Spatial Statistics, 49, 100549. (doi: 10.1016/j.spasta.2021.100549)

Merk, M. S. and Otto, P. (2022) Estimation of the spatial weighting matrix for regular lattice data—An adaptive lasso approach with cross-sectional resampling. Environmetrics, 33(1), e2705. (doi: 10.1002/env.2705)

Malinovskaya, A., Otto, P. and Peters, T. (2022) Statistical learning for change point and anomaly detection in graphs. In: Steland, Ansgar and Tsui, Kwok-Leung (eds.) Artificial Intelligence, Big Data and Data Science in Statistics. Springer, pp. 85-109. ISBN 9783031071553 (doi: 10.1007/978-3-031-07155-3_4)

2021

Otto, P. , Piter, A. and Gijsman, R. (2021) Statistical analysis of beach profiles – A spatiotemporal functional approach. Coastal Engineering, 170, 103999. (doi: 10.1016/j.coastaleng.2021.103999)

Malinovskaya, A. and Otto, P. (2021) Online network monitoring. Statistical Methods and Applications, 30, pp. 1337-1364. (doi: 10.1007/s10260-021-00589-z)

Otto, P. , Schmid, W. and Garthoff, R. (2021) Stochastic properties of spatial and spatiotemporal ARCH models. Statistical Papers, 62(2), pp. 623-638. (doi: 10.1007/s00362-019-01106-x)

Merk, M.S. and Otto, P. (2021) Directional spatial autoregressive dependence in the conditional first- and second-order moments. Spatial Statistics, 41, 100490. (doi: 10.1016/j.spasta.2020.100490)

Antoniuk, A., Merk, M. S. and Otto, P. (2021) Spatial statistics, or how to extract knowledge from data. In: Werner, Martin and Chiang, Yao-Yi (eds.) Handbook of Big Geospatial Data. Springer, pp. 399-426. ISBN 9783030554620 (doi: 10.1007/978-3-030-55462-0_15)

Otto, P. (2021) Parallelized monitoring of dependent spatiotemporal processes. In: Knoth, Sven and Schmid, Wolfgang (eds.) Frontiers in Statistical Quality Control 13. Springer, pp. 165-183. ISBN 9783030678562 (doi: 10.1007/978-3-030-67856-2_10)

2020

Merk, M. S. and Otto, P. (2020) Estimation of anisotropic, time-varying spatial spillovers of fine particulate matter due to wind direction. Geographical Analysis, 52(2), pp. 254-277. (doi: 10.1111/gean.12205)

2019

Otto, P. (2019) spGARCH: An R-package for spatial and spatiotemporal ARCH and GARCH models. R Journal, 11(2), pp. 401-420.

Otto, P. (2019) Modeling Spatial Dependence in Local Risks and Uncertainties. In: 29th European Safety and Reliability Conference, ESREL 2019, Hannover, Germany, 22 September-26 September 2019, pp. 2685-2692. ISBN 9789811127243

Otto, P. (2019) Parallelized Monitoring of Dependent Spatiotemporal Processes. In: 13th International Workshop on Intelligent Statistical Quality Control, IWISQC 2019, Hong Kong, 12 - 14 August 2019, pp. 181-194.

2018

Otto, P. and 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), pp. 452-456. (doi: 10.1002/asmb.2360)

Garthoff, R. and Otto, P. (2018) Verfahren zur Überwachung räumlicher autoregressiver Prozesse mit externen Regressoren = Statistical surveillance of spatial autoregressive processes with exogenous regressors. AStA Wirtschafts- und Sozialstatistisches Archiv, 12(2), pp. 107-133. (doi: 10.1007/s11943-018-0224-1)

2017

Otto, P. (2017) A note on efficient simulation of multidimensional spatial autoregressive processes. Communications in Statistics: Simulation and Computation, 46(6), pp. 4547-4558. (doi: 10.1080/03610918.2015.1122050)

Otto, P. and Lange, A.-L. (2017) Arbeitsbuch der Angewandten Statistik: Mit Aufgaben zur Software R und detaillierten Lösungen. Springer Gabler: Berlin, Heidelberg. ISBN 9783662492116 (doi: 10.1007/978-3-662-49212-3)

2016

Lange, A.-L. and Otto, P. (2016) Bayes’sche Statistik in der Dienstleistungsforschung. AStA Wirtschafts- und Sozialstatistisches Archiv, 10(4), pp. 247-267. (doi: 10.1007/s11943-016-0189-x)

Otto, P. and Schmid, W. (2016) Spatiotemporal analysis of German real-estate prices. Annals of Regional Science, 60, pp. 41-72. (doi: 10.1007/s00168-016-0789-y)

Otto, P. (2016) Detection of spatial change points in the mean and covariances of multivariate simultaneous autoregressive models. Biometrical Journal, 58(5), pp. 1113-1137. (doi: 10.1002/bimj.201500148)

Otto, P. and Schmid, W. (2016) Detection of spatial change points in the mean and covariances of multivariate simultaneous autoregressive models. Biometrical Journal, 58(5), pp. 1113-1137. (doi: 10.1002/bimj.201500148)

Garthoff, R. and Otto, P. (2016) Control charts for multivariate spatial autoregressive models. AStA Advances in Statistical Analysis, 101, pp. 67-94. (doi: 10.1007/s10182-016-0276-x)

2015

Garthoff, R. and Otto, P. (2015) Simultaneous surveillance of means and covariances of spatial models. In: Steland, A., Rafajłowicz, E. and Szajowski, K. (eds.) Stochastic Models, Statistics and Their Applications. Series: Springer proceedings in mathematics and statistics (122). Springer: Cham, pp. 271-281. ISBN 9783319138800 (doi: 10.1007/978-3-319-13881-7_30)

Articles

Colombo, P., Mattera, R. and Otto, P. (2025) Simple yet effective: a comparative study of statistical models for yearly hurricane forecasting. Environmetrics, 36(3), e70009. (doi: 10.1002/env.70009)

Otto, P. (2025) Discussion on “Assessing predictability of environmental time series with statistical and machine learning models” by Bonas et al. Environmetrics, 36(2), e2898. (doi: 10.1002/env.2898)

Belbe, Ș., Moldovan, D., Andrieș, A. M., Otto, P. and 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, 63, 101209. (doi: 10.1016/j.ememar.2024.101209)

Dorau, K., Rückamp, D., Weber, C., Scheeder, G., Reßing, R., Peth, S., Otto, P. , Altmann, K., Fries, E. and Hoppe, M. (2024) Characterization and spatial distribution of mesoplastics in an arable soil. European Journal of Soil Science, 75(6), e70016. (doi: 10.1111/ejss.70016)

Otto, P. , Fasso, A. and Maranzano, P. (2024) A review of regularised estimation methods and cross-validation in spatiotemporal statistics. Statistics Surveys, (Accepted for Publication)

Mattera, R. and Otto, P. (2024) Network log-ARCH models for forecasting stock market volatility. International Journal of Forecasting, 40(4), pp. 1539-1555. (doi: 10.1016/j.ijforecast.2024.01.002)

Khoo, T. H., Pathmanathan, D., Otto, P. and Dabo‐Niang, S. (2024) A Markov‐switching spatio‐temporal ARCH model. Stat, 13(3), e713. (doi: 10.1002/sta4.713)

Otto, P. , Doğan, O., Taspinar, S., Schmid, W. and Bera, A. (2024) Spatial and spatiotemporal volatility models: a review. Journal of Economic Surveys, (doi: 10.1111/joes.12643) (Early Online Publication)

Otto, P. (2024) A multivariate spatial and spatiotemporal ARCH model. Spatial Statistics, 60, 100823. (doi: 10.1016/j.spasta.2024.100823)

Mohammadi, R., Taleai, M., Otto, P. and Sester, M. (2024) Analyzing urban crash incidents: an advanced endogenous approach using spatiotemporal weights matrix. Transactions in GIS, 28(2), pp. 368-410. (doi: 10.1111/tgis.13138)

Otto, P. , Doğan, O. and Taşpınar, S. (2024) Dynamic spatiotemporal ARCH models. Spatial Economic Analysis, 19(2), pp. 250-271. (doi: 10.1080/17421772.2023.2254817)

Otto, P. , Fusta Moro, A., Rodeschini, J., Shaboviq, Q., Ignaccolo, R., Golini, N., Cameletti, M., Maranzano, P., Finazzi, F. and Fassò, A. (2024) Spatiotemporal modelling of PM2.5 concentrations in Lombardy (Italy): a comparative study. Environmental and Ecological Statistics, (doi: 10.1007/s10651-023-00589-0) (Early Online Publication)

Malinovskaya, A., Mozharovskyi, P. and Otto, P. (2024) Statistical process monitoring of artificial neural networks. Technometrics, 66(1), pp. 104-117. (doi: 10.1080/00401706.2023.2239886)

Fülle, M. J. and Otto, P. (2024) Spatial GARCH models for unknown spatial locations – an application to financial stock returns. Spatial Economic Analysis, 19(1), pp. 92-105. (doi: 10.1080/17421772.2023.2237067)

Otto, P. , Doğan, O. and Taşpınar, S. (2023) A dynamic spatiotemporal stochastic volatility model with an application to environmental risks. Econometrics and Statistics, (doi: 10.1016/j.ecosta.2023.11.002) (In Press)

Otto, P. and 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), pp. 696-711. (doi: 10.1080/10618600.2022.2107530)

Fassò, A., Rodeschini, J., Fusta Moro, A., Shaboviq, Q., Maranzano, P., Cameletti, M., Finazzi, F., Golini, N., Ignaccolo, R. and Otto, P. (2023) Agrimonia: a dataset on livestock, meteorology and air quality in the Lombardy region, Italy. Scientific Data, 10(1), 143. (doi: 10.1038/s41597-023-02034-0) (PMID:36934159) (PMCID:PMC10024000)

Harke, F. and Otto, P. (2023) Solar self-sufficient households as a driving factor for sustainability transformation. Sustainability, 15(3), 2734. (doi: 10.3390/su15032734)

Otto, P. and Otto, P. (2023) What’s in a name? Significance, 20(1), pp. 34-37. (doi: 10.1093/jrssig/qmad010)

Garthoff, R. and Otto, P. (2022) Spatiotemporal procedures for the statistical surveillance of spatial autoregressive models with heavy tails. Communications in Statistics: Simulation and Computation, 51(10), pp. 5709-5737. (doi: 10.1080/03610918.2020.1779294)

Otto, P. and Schmid, W. (2022) A general framework for spatial GARCH models. Statistical Papers, (doi: 10.1007/s00362-022-01357-1) (Early Online Publication)

Otto, P. and Otto, P. (2022) Impact of academic authorship characteristics on article citations. Revstat Statistical Journal, 20(4), pp. 427-447. (doi: 10.57805/revstat.v20i4.382)

Harke, F. H., Merk, M. S. and Otto, P. (2022) Estimation of Asymmetric Spatial Autoregressive Dependence on Irregular Lattices. Symmetry, 14(7), 1474. (doi: 10.3390/sym14071474)

Piter, A., Otto, P. and Alkhatib, H. (2022) The Helsinki bike‐sharing system—Insights gained from a spatiotemporal functional model. Journal of the Royal Statistical Society: Series A (Statistics in Society), 185(3), pp. 1294-1318. (doi: 10.1111/rssa.12834)

Fassò, A., Maranzano, P. and Otto, P. (2022) Spatiotemporal variable selection and air quality impact assessment of COVID-19 lockdown. Spatial Statistics, 49, 100549. (doi: 10.1016/j.spasta.2021.100549)

Merk, M. S. and Otto, P. (2022) Estimation of the spatial weighting matrix for regular lattice data—An adaptive lasso approach with cross-sectional resampling. Environmetrics, 33(1), e2705. (doi: 10.1002/env.2705)

Otto, P. , Piter, A. and Gijsman, R. (2021) Statistical analysis of beach profiles – A spatiotemporal functional approach. Coastal Engineering, 170, 103999. (doi: 10.1016/j.coastaleng.2021.103999)

Malinovskaya, A. and Otto, P. (2021) Online network monitoring. Statistical Methods and Applications, 30, pp. 1337-1364. (doi: 10.1007/s10260-021-00589-z)

Otto, P. , Schmid, W. and Garthoff, R. (2021) Stochastic properties of spatial and spatiotemporal ARCH models. Statistical Papers, 62(2), pp. 623-638. (doi: 10.1007/s00362-019-01106-x)

Merk, M.S. and Otto, P. (2021) Directional spatial autoregressive dependence in the conditional first- and second-order moments. Spatial Statistics, 41, 100490. (doi: 10.1016/j.spasta.2020.100490)

Merk, M. S. and Otto, P. (2020) Estimation of anisotropic, time-varying spatial spillovers of fine particulate matter due to wind direction. Geographical Analysis, 52(2), pp. 254-277. (doi: 10.1111/gean.12205)

Otto, P. (2019) spGARCH: An R-package for spatial and spatiotemporal ARCH and GARCH models. R Journal, 11(2), pp. 401-420.

Otto, P. and 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), pp. 452-456. (doi: 10.1002/asmb.2360)

Garthoff, R. and Otto, P. (2018) Verfahren zur Überwachung räumlicher autoregressiver Prozesse mit externen Regressoren = Statistical surveillance of spatial autoregressive processes with exogenous regressors. AStA Wirtschafts- und Sozialstatistisches Archiv, 12(2), pp. 107-133. (doi: 10.1007/s11943-018-0224-1)

Otto, P. (2017) A note on efficient simulation of multidimensional spatial autoregressive processes. Communications in Statistics: Simulation and Computation, 46(6), pp. 4547-4558. (doi: 10.1080/03610918.2015.1122050)

Lange, A.-L. and Otto, P. (2016) Bayes’sche Statistik in der Dienstleistungsforschung. AStA Wirtschafts- und Sozialstatistisches Archiv, 10(4), pp. 247-267. (doi: 10.1007/s11943-016-0189-x)

Otto, P. and Schmid, W. (2016) Spatiotemporal analysis of German real-estate prices. Annals of Regional Science, 60, pp. 41-72. (doi: 10.1007/s00168-016-0789-y)

Otto, P. (2016) Detection of spatial change points in the mean and covariances of multivariate simultaneous autoregressive models. Biometrical Journal, 58(5), pp. 1113-1137. (doi: 10.1002/bimj.201500148)

Otto, P. and Schmid, W. (2016) Detection of spatial change points in the mean and covariances of multivariate simultaneous autoregressive models. Biometrical Journal, 58(5), pp. 1113-1137. (doi: 10.1002/bimj.201500148)

Garthoff, R. and Otto, P. (2016) Control charts for multivariate spatial autoregressive models. AStA Advances in Statistical Analysis, 101, pp. 67-94. (doi: 10.1007/s10182-016-0276-x)

Books

Otto, P. and Lange, A.-L. (2017) Arbeitsbuch der Angewandten Statistik: Mit Aufgaben zur Software R und detaillierten Lösungen. Springer Gabler: Berlin, Heidelberg. ISBN 9783662492116 (doi: 10.1007/978-3-662-49212-3)

Book Sections

Malinovskaya, A., Otto, P. and Peters, T. (2022) Statistical learning for change point and anomaly detection in graphs. In: Steland, Ansgar and Tsui, Kwok-Leung (eds.) Artificial Intelligence, Big Data and Data Science in Statistics. Springer, pp. 85-109. ISBN 9783031071553 (doi: 10.1007/978-3-031-07155-3_4)

Antoniuk, A., Merk, M. S. and Otto, P. (2021) Spatial statistics, or how to extract knowledge from data. In: Werner, Martin and Chiang, Yao-Yi (eds.) Handbook of Big Geospatial Data. Springer, pp. 399-426. ISBN 9783030554620 (doi: 10.1007/978-3-030-55462-0_15)

Otto, P. (2021) Parallelized monitoring of dependent spatiotemporal processes. In: Knoth, Sven and Schmid, Wolfgang (eds.) Frontiers in Statistical Quality Control 13. Springer, pp. 165-183. ISBN 9783030678562 (doi: 10.1007/978-3-030-67856-2_10)

Garthoff, R. and Otto, P. (2015) Simultaneous surveillance of means and covariances of spatial models. In: Steland, A., Rafajłowicz, E. and Szajowski, K. (eds.) Stochastic Models, Statistics and Their Applications. Series: Springer proceedings in mathematics and statistics (122). Springer: Cham, pp. 271-281. ISBN 9783319138800 (doi: 10.1007/978-3-319-13881-7_30)

Edited Books

Knoth, S., Okhrin, Y. and Otto, P. (Eds.) (2024) Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science: Essays in Honour of Wolfgang Schmid. Springer: Cham. ISBN 9783031691102 (In Press)

Conference Proceedings

Otto, P. (2019) Modeling Spatial Dependence in Local Risks and Uncertainties. In: 29th European Safety and Reliability Conference, ESREL 2019, Hannover, Germany, 22 September-26 September 2019, pp. 2685-2692. ISBN 9789811127243

Otto, P. (2019) Parallelized Monitoring of Dependent Spatiotemporal Processes. In: 13th International Workshop on Intelligent Statistical Quality Control, IWISQC 2019, Hong Kong, 12 - 14 August 2019, pp. 181-194.