Papers (2015–)

Technical Reports & Papers submitted to International Journals.

1. Alegria, A. and Porcu, E. (2017). Space-Time Geostatistical Models with both Linear and Seasonal Structures in the Temporal Components. Technical Report, UTFSM.
2. Ferreira, G., Lagos, B., Porcu, E. and Mateu, J. (2017). Prediction Intervals in Locally Stationary Processes through Bootstrap Techniques. Submitted.
3. Cleanthous, G., Georgiadis, A. and Porcu, E. (2019). Minimax density estimation on  metric spaces. Technical Report, Trinity College Dublin.
4. Alegria, A., Cleanthous, G., Georgiadis, Porcu, E. and, White, P. (2021). Random Fields on the Hypertorus: Theory and Applications. Submitted. 
5. Cornejo-Porcile, A., Correa-Fuentes, S., Lima-Velásquez, M., Ovando-Vidal, S., Cid, M.A., Porcu, E, Zepeda, R., Gallardo-Garrido, C. (2020). Priorization of patients with pneumonia caused by SARS-COV-2: Clinical Score at emergency room. Submitted.
6. Malyarenko, A. and Porcu, E. (2021). Multivariate Random Fields evolving temporally over the Hypertorus. Submitted.
7. López do Prado, M., Peron, A. and Porcu, E. (2021). Dimension Walks over Generalized Spaces. Submitted.
8. Emery, X. and Porcu, E. (2022). Integral Representations, Extension Theorems and Walks through Dimensions under Radial Exponential Convexity.
9. Bissiri, P.G. and Porcu, E. (2022). Nonparametric Bayesian Modeling of Covariance Functions on Spheres cross Time. Submitted.
10. Ostoja-Starzewski, M. and Porcu, E. (2022). Fractal and Hurst effects in Stochastic Mechanics. A review. Submitted.
11. Porcu, E., White, P. and Genton, M. (2022). Nonseparable Space-Time Stationary Covariance Functions on Networks cross time. Submitted.
12. Alegria, A. and Porcu, E. (2022). Hybrid Parametric Classes of Isotropic Covariance Functions for Spatial Random Fields. Submitted. Waiting for the PLR soon.
13. Ferreira, V., Porcu, E. and Zubelli, J. (2022). Random Fields on Hilbert spaces with their Equivalent Gaussian Measures. Submitted.
14. Emery, X., Mery, N. and Porcu, E. Vector-Valued Gaussian Processes on Non-Euclidean Product Spaces: Constructive Methods and Fast Simulations based on Partial Spectral Inversion. Submitted.
15. Porcu, E., White, P. and Genton, M. (2022). Nonseparable Space-Time Stationary Covariance Functions on Networks cross Time. Submitted.
16. Porcu, E., Bevilacqua, M., Schaback, R. and Oates, C. (2023). The Mat\’ern Model: A Journey through Statistics, Numerical Analysis and Machine Learning. Submitted.
17. Henschel, A., Saif-Ali, R., Al-Habori, M., Kamarul, M., Pagani, L., Al Hageh, C., Porcu, E., Taleb, N., Platt, D. and Zalloua, P. (2023). Post Last Glacial Period witnessed Significant Human Mobility from the Levant into Yemen.
18. Faouzi, T., Furrer, R. and Porcu, E. (2023). Compatibility of Space-Time Kernels with Full, Dynamical, or Compact Support.

Published

2023.

1. Faouzi, T., Porcu, E., Kondrashuk, I. and Bevilacqua, M. (2023). Convergence arguments to bridge Cauchy and Matérn covariance functions. Statistical Papers. Accepted.
2. Emery, X. and Porcu, E. (2023). Extending the Gneiting class for modeling spatially isotropic and temporally symmetric vector random fields. Journal of Mathematical Analysis and Applications. Accepted.
3. Emery, X. and Porcu, E. (2022). The Schoenberg Kernel and More Flexible Multivariate Covariance Models in Euclidean spaces. Computational and Applied Mathematics. Accepted.
4. Hubbert, S., Porcu, E., Oates, C. and Girolami, M. (2022). Sobolev spaces, Kernels and Discrepancies over Hyperspheres. Transactions on Machine Learning Research. Accepted.
5. Jetti, Y.S, Porcu, E. and Ostoja Starzewski, M. (2022). Decouplers of Fractal Dimensions and Hurst Effects: New Models, with application to MOSP. Zeitschrift fur Angewandte Mathematik und Physik. Accepted.

2022.

1. Bevilacqua, M., Caamaño, C. and Porcu, E. (2022). Unifying Compactly Supported and Matérn Covariance Functions in Spatial Statistics. Journal of Multivariate Analysis. Accepted.
2. Caraballo, T., Piña, J. and Porcu, E. (2021). A Stochastic Fractional Laplace Equation driven by colored noise on Bounded Domain, and its Covariance Functional. Stochastic Models. Accepted.
3. Emery, X., Porcu, E. and White, P. (2021). New validity conditions for the multivariate Matérn coregionalization model, with an application to exploration geochemistry. Mathematical Geology. Accepted.
4. Giraldo, R., Ramirez, A. and Porcu, E. (2020). A Normality Test in Geostatistics Based on Mahalanobis Distance. Ciencia en Desarrollo. Accepted.
5. Cleanthous, G., Georgiadis, A. and Porcu, E. (2020). Oracle inequalities and upper bounds for kernel density estimators on manifolds and more general metric spaces. Journal of Nonparametric Statistics. Accepted.
6. Blake, L., Porcu, E. and Hammerling, D. (2022). Parametric Nonstationary Covariance Functions on Spheres. Stat. Accepted.
7. Porcu, E., Feng, S., Emery, X. and Peron, A.P. (2021). Rudin Extensions Theorems on Product Spaces, Turning Bands, and Random Fields on Balls cross Time. Bernoulli. Accepted.
8. Porcu, E., Emery, X. and Mery, N. (2022). Criteria and Characterizations for Spatially Isotropic and Temporally Symmetric Matrix-Valued Covariance Functions. Computational and Applied Mathematics. Accepted.
9. Ferreira, G., Mateu, J., Porcu, E. (2022). Multivariate Kalman Filtering for Spatio-Temporal Processes. Stochastic Environmental Research Risk Assessment. Accepted.
10. Bissiri, P.G., Cleanthous, G., Emery, X., Nipoti, B. and Porcu, E. (2020). Nonparametric Bayesian Modelling of Longitudinally Integrated Covariance Functions on Spheres. Computational Statistics and Data Analysis. Accepted.
11. Barbosa, V., Gregori, P., Peron, A.P. and Porcu, E. (2021). Series expansions among spaces of positive definite functions on compact two-point homogeneous spaces. Journal of Mathematical Analysis and Applications. Accepted.
12. Porcu, E., Emery, X. and Peron, A. (2021). Nested Covariance Functions on Graphs with Euclidean Edges cross Time. Electronic Journal of Statistics.
13. Emery, X., Peron, A. and Porcu, E. (2022). A catalogue of Multivariate Covariance Models on Hypertori. Stochastic Environmental Research Risk Assessment. Accepted.
14. Emery, X., Mery, N., Khorram, F. and Porcu, E. (2021), Compactly-supported isotropic covariances on spheres obtained from matrix-valued covariances in Euclidean spaces. Constructive Approximation. Accepted.
15. Antouche, M., Lara Carrion, L., Porcu, E. and Bramstedt, K. (2022). The effect of the COVID-19 pandemic on deceased and living organ donors in the United States of America. Scientific Reports. Accepted.

2021.

1. Bachoc, F., Porcu, E., Bevilacqua, M., Furrer, R. and Faouzi. T. (2020). Asymptotically Equivalent Prediction in Multivariate Geostatistics. Bernoulli. Accepted.
2. Barp, A., Oates, C., Porcu, E. and Girolami, M. (2018). A Riemannian–Stein Kernel Method. Bernoulli. Accepted-
3. Alegría, A.A., Emery, X. and Porcu, E. (2020). Cross-Dimple for Isotropic Bivariate Random Fields with Mat\’ern Covariance Functions. Spatial Statistics. Accepted.
4. Faouzi, T., Porcu, E., Kondrachuk, I. and Malyarenko, A. (2021). A deep look into the Dagum family of isotropic covariance functions. Advances in Applied Probability. Accepted.
5. Cleanthous, G, Porcu, E. and White, P.A. (2020). Regularity and Approximation of Gaussian Random Fields Evolving Temporally over Compact Two-Point Homogeneous Spaces. Test. Accepted.
6. Laudani, R., Zhang, D., Faouzi, T., Chamorro, L., Porcu, E. and Ostoja-Starzewski, M. (2019). On the fractal and long-memory effects of turbulent velocity: theory and experiments. Physics of Fluids. Accepted.
7. Alegría, A., Bissiri, P.G., Cleanthous, G., Porcu, E. and White, P.A. (2020). Multivariate Isotropic Random Fields on Spheres: Nonparametric Bayesian Modeling and L^p Fast Approximations. Electronic Journal of Statistics. Accepted.
8. Alegria, A., Cuevas, F., Diggle, P. and Porcu, E. (2021). A new family of covariance functions on spheres. Spatial Statistics. Accepted.
9. Papalexiou, S., Serinaldi, F. and Porcu, E. (2020). Advancing Space-Time Simulation of Random Fields: From Storms to Cyclones and Beyond. Water Resources Research. Accepted.
10. Porcu, E. and White, P. (2020). Random Fields on the Hypertorus: Covariance Modeling and Applications. Environmetrics. Accepted.
11. Zhang, X., Malyarenko, A., Porcu, E., Ostoja-Starzewski, M. (2021). Elastodynamic problem on tensor random fields with fractal and Hurst effects. Meccanica. Accepted.
12. Bachoc, F., Peron, A. and Porcu, E. (2021). Multivariate Gaussian Random Fields over Generalized Product Spaces involving the Hypertorus. Theory of Probability and Mathematical Statistics. Accepted.
13. Emery, X., Peron, A.P. and Porcu, E. (2021). Dimension Walks over Hyperspheres. Computational and Applied Mathematics. Accepted.

2020.

1. Senoussi, R. and Porcu, E. (2020). Nonstationary Space-time Covariance Functions induced by Temporally Dynamical Spatial Diffeomorphisms. Scandinavian Journal of Statistics. Accepted.
2. Fouzi, T., Porcu, E. and Bevilacqua, M. (2020). Space-Time Estimation and Prediction under Infill Asymptotics with Compactly Supported Covariance Functions. Statistica Sinica. Accepted.
3. Cleanthous, G., Georgiadis, A. and Porcu, E. (2019). Minimax density estimation on Sobolev spaces with dominating mixed smoothness. Electronic Journal of Statistics. Accepted.
4. Porcu, E., Bissiri, P.G., Tagle, F.,Cornejo, R. and Quintana, F. (2018). Nonparametric Bayesian Modeling and Estimation of Spatial Correlation Functions for Global Data. Bayesian Analysis. Accepted.
5. Porcu, E., Zastavnyi, V.P., Bevilacqua, M. and Emery, X. (2019). Stein Hypothesis and Screening Effect for Covariances with Compact Support. Electronic Journal of Statistics. Accepted.
6. Porcu, E., Furrer, R. and Nychka, D. (2020). 30 Years of Space-Time Covariance Functions. WIREs Computational Statistics. Accepted.
7. Cleanthous, G., Georgiadis, A., Lang, A. and Porcu, E. (2020). Regularity, Continuity and Approximation of Isotropic Gaussian Random Fields on Compact Two-Point Homogeneous Spaces. Stochastic Processes and their Application. Accepted.
8. Porcu, E. Mendoza, E., Senoussi, R. and Bevilacqua, M. (2020). Covariance Functions over Spheres: the Reduction Problem via Deformations. Electronic Journal of Statistics. Accepted.
9. Faouzi, T., Porcu, E., Kondrachuk, I. and Bevilacqua, M. (2020). Zastavnyi operators and positive definite radial functions. Statistics and Probability Letters, 157, 108620.
10. Arafat, A., Gregori, P., & Porcu, E. (2020). Schoenberg coefficients and curvature at the origin of continuous isotropic positive definite kernels on spheres. Statistics & Probability Letters, 156, 108618.
11. Nishawala, V.V., Ostoja-Starzewski, M., Porcu, E. and Shen, L. (2020). Random fields with fractal and Hurst effects in mechanics. Encyclopedia of Continuum Mechanics. To appear. 
12. Menegatto, V., Oliveira, C. and Porcu, E. (2019). Gneiting Class, Semi-Metric Spaces, and Isometric Embeddings. Constructive Mathematical Analysis. To appear.
13. Porcu, E., Bevilacqua, M. and Genton, M.G. (2020). Nonseparable, Space-Time Covariance Functions with Dynamical Compact Supports. Statistica Sinica. Accepted.
14. Padilla, L. Lagos-Alvárez, B., Mateu, J. and Porcu, E. (2020). Space-time Autoregressive Estimation and Prediction in the Presence of Missing Data based on Kalman Filtering. Environmetrics. Accepted.
15. Bissiri, P.G., Peron, A.P. and Porcu, E. Strict Positive Definiteness under Axial Symmetry on the Sphere. Stochastic Environmental Research Risk Assessment. Accepted.
16. Bevilacqua, M., Diggle, P.J. and Porcu, E. (2019). Families of Covariance Functions for Bivariate Random Fields on Spheres. Spatial Statistics. Accepted.
17. Porcu, E., Rysgaard-Jensen, J. and Eveloy, V. (2020). Discussion on A high-resolution bilevel skew-t stochastic generator for assessing Saudi Arabia’s wind energy resources. Environmetrics. Accepted.

2019.

1. Bevilacqua, M., Faouzi, T., Furrer, R., & Porcu, E. (2019). Estimation and prediction using generalized wendland covariance functions under fixed domain asymptotics.  The Annals of Statistics, 47(2), 828-856.
2. Emery, X., Porcu, E. and Bissiri, P.G. (2019). A semiparametric class of axially symmetric random fields on the sphere. Stochastic Environmental Research Risk Assessment, 33, 10, 1863–1874.
3. Emery, X., & Porcu, E. (2019). Simulating isotropic vector-valued Gaussian random fields on the sphere through finite harmonics approximations. Stochastic Environmental Research and Risk Assessment, 33(8-9), 1659-1667.
4. White, P. and Porcu, E. (2019). Towards a Complete Picture of Covariance Functions on Spheres Cross Time. Electronic Journal of Statistics, 13, 2, 2566-2594.
5. Cuevas, F., Allard, D., & Porcu, E. (2019). Fast and exact simulation of Gaussian random fields defined on the sphere cross time. Statistics and Computing, 1-8.
6. Alegría, A., Porcu, E., Furrer, R., & Mateu, J. (2019). Covariance functions for multivariate Gaussian fields evolving temporally over planet earth. Stochastic Environmental Research and Risk Assessment, 33(8-9), 1593-1608.
7. Estrade, A., Fariñas, A., & Porcu, E. (2019). Covariance functions on spheres cross time: Beyond spatial isotropy and temporal stationarity. Statistics & Probability Letters, 151, 1-7.
8. Bissiri, P. G., Menegatto, V. A., & Porcu, E. (2019). Relations between Schoenberg Coefficients on Real and Complex Spheres of Different Dimensions. SIGMA. Symmetry, Integrability and Geometry: Methods and Applications, 15, 004.
9. Pineda-Ríos, W., Giraldo, R., & Porcu, E. (2019). Functional SAR models: With application to spatial econometrics.  Spatial statistics, 29, 145-159.
10. Porcu, E., Castruccio, S., Alegria, A., & Crippa, P. (2019). Axially symmetric models for global data: a journey between geostatistics and stochastic generators. Environmetrics, 30(1), e2555.
11. White, P. A., & Porcu, E. (2019). Nonseparable covariance models on circles cross time: A study of Mexico City ozone. Environmetrics, e2558.
12. Crudu, F., & Porcu, E. (2019). Z-estimators and auxiliary information for strong mixing processes. Stochastic environmental research and risk assessment, 33(1), 1-11.
13. Emery, X., Furrer, R. and Porcu, E. (2019). A Turning Bands Method for Simulating Isotropic Gaussian Random Fields on the Sphere. Statistics and Probability Letters, 144, 9–15. 

2018.

1. Møller, J., Nielsen, M., Porcu, E., & Rubak, E. (2018). Determinantal point process models on the sphere. Bernoulli, 24(2), 1171-1201.
2. Porcu, E., Bevilacqua, M., & Hering, A. S. (2018). The Shkarofsky‐Gneiting class of covariance models for bivariate Gaussian random fields. Stat, 7(1), e207.
3. Peron, A., Porcu, E., & Emery, X. (2018). Admissible nested covariance models over spheres cross time. Stochastic environmental research and risk assessment, 32(11), 3053-3066.
4. Canas Rodrigues, P. and Porcu, E. (2018) 2nd Latin American Conference on Statistical Computing.  Editorial, Journal of Statistical Computation and Simulation, 88:10, 1847-1849.
5. Arafat, A., Porcu, E., Bevilacqua, M., & Mateu, J. (2018). Equivalence and orthogonality of Gaussian measures on spheres. Journal of Multivariate Analysis, 167, 306-318.
6. Ferreira, G., Piña, N., & Porcu, E. (2018). Estimation of slowly time-varying trend function in long memory regression models. Journal of Statistical Computation and Simulation, 88(10), 1903-1920.
7. Guella, J. C., Menegatto, V. A., & Porcu, E. (2018). Strictly positive definite multivariate covariance functions on spheres. Journal of Multivariate Analysis, 166, 150-159.
8. Porcu, E., Alegria, A., & Furrer, R. (2018). Modeling temporally evolving and spatially globally dependent data. International Statistical Review, 86(2), 344-377.
9. Berg, C., Peron, A. P., & Porcu, E. (2018). Schoenberg’s theorem for real and complex Hilbert spheres revisited. Journal of Approximation Theory, 228, 58-78.
10. De la Cerda, J. C., Alegría, A., & Porcu, E. (2018). Regularity properties and simulations of Gaussian random fields on the sphere cross time. Electronic Journal of Statistics, 12(1), 399-426
11. Alegría, A., Porcu, E., & Furrer, R. (2018). Asymmetric matrix-valued covariances for multivariate random fields on spheres. Journal of Statistical Computation and Simulation, 88(10), 1850-1862.
12. Garcia-Perez, F.J., Lara Carrión, L. and Porcu, E. (2018). Discussion to Statistical challenges of administrative and transaction data. Journal of the Royal Statistical Society, A. 
13. Berg, C., Peron, A. P., & Porcu, E. (2018). Orthogonal expansions related to compact Gelfand pairs. Expositiones Mathematicae, 36(3-4), 259-277.
14. Coeurjolly, J. F., & Porcu, E. (2018). Fast and exact simulation of complex-valued stationary Gaussian processes through embedding circulant matrix. Journal of Computational and Graphical Statistics, 27(2), 278-290.
15. Ferreira, G., Mateu, J., & Porcu, E. (2018). Spatio-temporal analysis with short-and long-memory dependence: a state-space approach. Test, 27(1), 221-245.

2017.

1. Massa, E., Peron, A. P. and Porcu, E. (2017), Positive Definite Functions on Complex Spheres and their Walks through Dimensions, SIGMA 13 (2017), 088, 16 pages.
2. Alegría, A., & Porcu, E. (2017). The dimple problem related to space–time modeling under the Lagrangian framework. Journal of Multivariate Analysis, 162, 110-121.
3. Porcu, E., Zastavnyi, V. P., & Bevilacqua, M. (2017). Buhmann covariance functions, their compact supports, and their smoothness. Dolomites Research Notes on Approximation, 10(1).
4. Cuevas, F., Porcu, E., & Bevilacqua, M. (2017). Contours and dimple for the Gneiting class of space-time correlation functions. Biometrika, 104(4), 995-1001.
5. Alegría, A., Caro, S., Bevilacqua, M., Porcu, E., & Clarke, J. (2017). Estimating covariance functions of multivariate skew-Gaussian random fields on the sphere. Spatial Statistics, 22, 388-402.
6. Lagos, B., Porcu, E. and Lara, L. (2017). Discussion to the paper by Gelman and Hering. Journal of the Royal Statistical Society, A. 
7. Coeurjolly, J. F., & Porcu, E. (2017). Properties and Hurst exponent estimation of the circularly-symmetric fractional Brownian motion. Statistics & Probability Letters, 128, 21-27.
8. Porcu, E., Fassò, A., Barrientos, S., & Catalán, P. A. (2017). Seismomatics. Stochastic Environmental Research and Risk Assessment, 31(7), 1577-1582.
9. Barca, E., Porcu, E., Bruno, D., & Passarella, G. (2017). An automated decision support system for aided assessment of variogram models. Environmental modelling & software, 87, 72-83.
10. Zastavnyi, V. P., & Porcu, E. (2017). On positive definiteness of some radial functions. Lobachevskii Journal of Mathematics, 38(2), 386-394.
11. Berg, C., & Porcu, E. (2017). From Schoenberg coefficients to Schoenberg functions. Constructive Approximation, 45(2), 217-241.
12. Alonso-Malaver, C. E., Porcu, E., & Henao, R. G. (2017). Multivariate versions of dimension walks and Schoenberg measures. Brazilian Journal of Probability and Statistics, 31(1), 144-159.

2016.

1. Porcu, E., Bevilacqua, M., & Genton, M. G. (2016). Spatio-temporal covariance and cross-covariance functions of the great circle distance on a sphere. Journal of the American Statistical Association, 111(514), 888-898.
2. Nishawala, V. V., Ostoja-Starzewski, M., Leamy, M. J., & Porcu, E. (2016). Lamb’s problem on random mass density fields with fractal and Hurst effects. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 472(2196), 20160638.
3. Guest Editors’ Introduction to the Special Issue on “Seismomatics: Space–Time Analysis of Natural or Anthropogenic Catastrophes”. Journal of agricultural, biological, and environmental statistics, 21(3), 403-406.
4. Emery, X., Arroyo, D., & Porcu, E. (2016). An improved spectral turning-bands algorithm for simulating stationary vector Gaussian random fields. Stochastic environmental research and risk assessment, 30(7), 1863-1873.
5. Bevilacqua, M., Fassò, A., Gaetan, C., Porcu, E., & Velandia, D. (2016). Covariance tapering for multivariate Gaussian random fields estimation. Statistical Methods & Applications, 25(1), 21-37.
6. Hering, A.S., Bevilacqua, M. and Porcu, E. (2016). Comment on the paper “Statistical modelling of citation exchange between statistics journals” by  C.~Varin, M.~Cattelan, and D.~Firth, J. R. Statist. Soc. A, 179: 1–33.
7. Allard, D., Senoussi, R., & Porcu, E. (2016). Anisotropy models for spatial data. Mathematical Geosciences, 48(3), 305-328.
8. Khosravi, M., Leiva, V., Jamalizadeh, A., & Porcu, E. (2016). On a nonlinear Birnbaum–Saunders model based on a bivariate construction and its characteristics. Communications in Statistics-Theory and Methods, 45(3), 772-793.

2015.

1. Shen, L., Ostoja-Starzewski, M., & Porcu, E. (2015). Harmonic oscillator driven by random processes having fractal and Hurst effects. Acta Mechanica, 226(11), 3653-3672.
2. Bevilacqua, M., Hering, A. S., & Porcu, E. (2015). On the flexibility of multivariate covariance models: comment on the paper by Genton and Kleiber. Statistical Science, 30(2), 167-169.
3. Castro, D. and Porcu, E. (2015). Discussion on the paper by Gerber and Chopin. Journal of the Royal Statistical Society, B. 
4. Salazar, E., Giraldo, R., & Porcu, E. (2015). Spatial prediction for infinite-dimensional compositional data. Stochastic environmental research and risk assessment, 29(7), 1737-1749.
5. Daley, D. J., Porcu, E., & Bevilacqua, M. (2015). Classes of compactly supported covariance functions for multivariate random fields. Stochastic environmental research and risk assessment, 29(4), 1249-1263.
6. Alonso-Malaver, C. E., Porcu, E., & Giraldo, R. (2015). Multivariate and multiradial Schoenberg measures with their dimension walks. Journal of Multivariate Analysis, 133, 251-265.
7. Ruiz-Medina, M. D., & Porcu, E. (2015). Equivalence of Gaussian measures of multivariate random fields. Stochastic environmental research and risk assessment, 29(2), 325-334.
8. Bevilacqua, M., Crudu, F., & Porcu, E. (2015). Combining Euclidean and composite likelihood for binary spatial data estimation. Stochastic environmental research and risk assessment, 29(2), 335-346.
9. Shen, L., Ostoja-Starzewski, M., & Porcu, E. (2015). Elastic rods and shear beams with random field properties under random field loads: fractal and Hurst effects. Journal of Engineering Mechanics, 141(7), 04015002.
10. Kleiber, W., & Porcu, E. (2015). Nonstationary matrix covariances: compact support, long range dependence and quasi-arithmetic constructions. Stochastic environmental research and risk assessment, 29(1), 193-204.
11. Fassò, A., & Porcu, E. (2015). Latent variables and space-time models for environmental problems. Stochastic environmental research and risk assessment, 29, 323-324.
12. Shen, L., Ostoja-Starzewski, M., & Porcu, E. (2015). Responses of first-order dynamical systems to matérn, cauchy, and Dagum excitations. Mathematics and Mechanics of Complex Systems, 3(1), 27-41.