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. Ferreira, G., Mateu, J., Porcu, E. and Alegria, A. (2018). Multivariate Kalman Filtering for Spatio-Temporal Processes. Submitted.
  4. Barp, A., Oates, C., Porcu, E. and Girolami, M. (2018). A Riemannian–Stein Kernel Method. Submitted.
  5. Giraldo, R., Ramirez, A. and Porcu, E. (2020). A Normality Test in Geostatistics Based on Mahalanobis Distance. Submitted.
  6. Cleanthous, G., Georgiadis, A. and Porcu, E. (2019). Minimax density estimation on  metric spaces. Technical Report, Trinity College Dublin.
  7. Alegria, A., Cleanthous, G., Georgiadis, Porcu, E. and, White, P. (2021). Random Fields on the Hypertorus: Theory and Applications. Submitted. 
  8. Porcu, E. and White, P. (2020). Random Fields on the Hypertorus: Covariance Modeling and Applications. Submitted.
  9. Cleanthous, G., Georgiadis, A. and Porcu, E. (2020). Oracle inequalities and upper bounds for kernel density estimators on manifolds and more general metric spaces. Submitted.
  10. Alegria, A., Cuevas, F., Diggle, P. and Porcu, E. (2018). A new family of covariance functions on spheres. Submitted.
  11. Bachoc, F., Porcu, E., Bevilacqua, M., Furrer, R. and Faouzi. T. (2020). Asymptotically Equivalent Prediction in Multivariate Geostatistics. Submitted.
  12. Bissiri, P.G., Cleanthous, G., Emery, X., Nipoti, B. and Porcu, E. (2020). Nonparametric Bayesian Modelling of Longitudinally Integrated Covariance Functions on Spheres. Submitted.
  13. 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.
  14. Papalexiou, S., Serinaldi, F. and Porcu, E. (2020). Submitted.
  15. Caraballo, T., Piña, J. and Porcu, E. (2021). A Stochastic Fractional Laplace Equation driven by colored noise on Bounded Domain, and its Covariance Functional. Submitted.
  16. Zhang, X., Malyarenko, A., Porcu, E., Ostoja-Starzewski, M. (2021). Elastodynamic problem on tensor random fields with fractal and Hurst effects. Submitted.
  17. Malyarenko, A. and Porcu, E. (2021). Multivariate Random Fields evolving temporally over the Hypertorus. Submitted.
  18. Barbosa, V., Gregori, P., Peron, A. and Porcu, E. (2021). Gneiting’s problems over compact two-point homogeneous spaces. Submitted.



  1. Alegría, A.A., Emery, X. and Porcu, E. (2020). Cross-Dimple for Isotropic Bivariate Random Fields with Mat\’ern Covariance Functions. Spatial Statistics. Accepted.
  2. 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.
  3. 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.
  4. 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.


  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 spheresStatistics & Probability Letters156, 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 SupportsStatistica 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.


  1. Bevilacqua, M., Faouzi, T., Furrer, R., & Porcu, E. (2019). Estimation and prediction using generalized wendland covariance functions under fixed domain asymptoticsThe Annals of Statistics47(2), 828-856.
  2. Emery, X., Porcu, E. and Bissiri, P.G. (2019). A semiparametric class of axially symmetric random fields on the sphereStochastic 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 approximationsStochastic Environmental Research and Risk Assessment33(8-9), 1659-1667.
  4. White, P. and Porcu, E. (2019). Towards a Complete Picture of Covariance Functions on Spheres Cross TimeElectronic 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 timeStatistics and Computing, 1-8.
  6. Alegría, A., Porcu, E., Furrer, R., & Mateu, J. (2019). Covariance functions for multivariate Gaussian fields evolving temporally over planet earthStochastic Environmental Research and Risk Assessment33(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 Letters151, 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 Applications15, 004.
  9. Pineda-Ríos, W., Giraldo, R., & Porcu, E. (2019). Functional SAR models: With application to spatial econometricsSpatial statistics29, 145-159.
  10. Porcu, E., Castruccio, S., Alegria, A., & Crippa, P. (2019). Axially symmetric models for global data: a journey between geostatistics and stochastic generatorsEnvironmetrics30(1), e2555.
  11. White, P. A., & Porcu, E. (2019). Nonseparable covariance models on circles cross time: A study of Mexico City ozoneEnvironmetrics, e2558.
  12. Crudu, F., & Porcu, E. (2019). Z-estimators and auxiliary information for strong mixing processesStochastic environmental research and risk assessment33(1), 1-11.
  13. Emery, X., Furrer, R. and Porcu, E. (2019). A Turning Bands Method for Simulating Isotropic Gaussian Random Fields on the SphereStatistics and Probability Letters, 144, 9–15. 


  1. Møller, J., Nielsen, M., Porcu, E., & Rubak, E. (2018). Determinantal point process models on the sphereBernoulli, 24(2), 1171-1201.
  2. Porcu, E., Bevilacqua, M., & Hering, A. S. (2018). The Shkarofsky‐Gneiting class of covariance models for bivariate Gaussian random fieldsStat7(1), e207.
  3. Peron, A., Porcu, E., & Emery, X. (2018). Admissible nested covariance models over spheres cross timeStochastic environmental research and risk assessment32(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 spheresJournal of Multivariate Analysis167, 306-318.
  6. Ferreira, G., Piña, N., & Porcu, E. (2018). Estimation of slowly time-varying trend function in long memory regression modelsJournal of Statistical Computation and Simulation88(10), 1903-1920.
  7. Guella, J. C., Menegatto, V. A., & Porcu, E. (2018). Strictly positive definite multivariate covariance functions on spheresJournal of Multivariate Analysis166, 150-159.
  8. Porcu, E., Alegria, A., & Furrer, R. (2018). Modeling temporally evolving and spatially globally dependent dataInternational Statistical Review86(2), 344-377.
  9. Berg, C., Peron, A. P., & Porcu, E. (2018). Schoenberg’s theorem for real and complex Hilbert spheres revisitedJournal of Approximation Theory228, 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 timeElectronic Journal of Statistics12(1), 399-426
  11. Alegría, A., Porcu, E., & Furrer, R. (2018). Asymmetric matrix-valued covariances for multivariate random fields on spheresJournal of Statistical Computation and Simulation88(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 pairsExpositiones Mathematicae36(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 Statistics27(2), 278-290.
  15. Ferreira, G., Mateu, J., & Porcu, E. (2018). Spatio-temporal analysis with short-and long-memory dependence: a state-space approachTest27(1), 221-245.


  1. Massa, E., Peron, A. P. and Porcu, E. (2017), Positive Definite Functions on Complex Spheres and their Walks through DimensionsSIGMA 13 (2017), 088, 16 pages.
  2. Alegría, A., & Porcu, E. (2017). The dimple problem related to space–time modeling under the Lagrangian frameworkJournal of Multivariate Analysis162, 110-121.
  3. Porcu, E., Zastavnyi, V. P., & Bevilacqua, M. (2017). Buhmann covariance functions, their compact supports, and their smoothnessDolomites Research Notes on Approximation10(1).
  4. Cuevas, F., Porcu, E., & Bevilacqua, M. (2017). Contours and dimple for the Gneiting class of space-time correlation functionsBiometrika104(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 sphereSpatial Statistics22, 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 Letters128, 21-27.
  8. Porcu, E., Fassò, A., Barrientos, S., & Catalán, P. A. (2017). SeismomaticsStochastic Environmental Research and Risk Assessment31(7), 1577-1582.
  9. Barca, E., Porcu, E., Bruno, D., & Passarella, G. (2017). An automated decision support system for aided assessment of variogram modelsEnvironmental modelling & software87, 72-83.
  10. Zastavnyi, V. P., & Porcu, E. (2017). On positive definiteness of some radial functionsLobachevskii Journal of Mathematics38(2), 386-394.
  11. Berg, C., & Porcu, E. (2017). From Schoenberg coefficients to Schoenberg functionsConstructive Approximation45(2), 217-241.
  12. Alonso-Malaver, C. E., Porcu, E., & Henao, R. G. (2017). Multivariate versions of dimension walks and Schoenberg measuresBrazilian Journal of Probability and Statistics, 31(1), 144-159.


  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 Association111(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 effectsProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences472(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 statistics21(3), 403-406.
  4. Emery, X., Arroyo, D., & Porcu, E. (2016). An improved spectral turning-bands algorithm for simulating stationary vector Gaussian random fieldsStochastic environmental research and risk assessment30(7), 1863-1873.
  5. Bevilacqua, M., Fassò, A., Gaetan, C., Porcu, E., & Velandia, D. (2016). Covariance tapering for multivariate Gaussian random fields estimationStatistical Methods & Applications25(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 dataMathematical Geosciences48(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 Methods45(3), 772-793.


  1. Shen, L., Ostoja-Starzewski, M., & Porcu, E. (2015). Harmonic oscillator driven by random processes having fractal and Hurst effectsActa Mechanica226(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 KleiberStatistical Science30(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 dataStochastic environmental research and risk assessment29(7), 1737-1749.
  5. Daley, D. J., Porcu, E., & Bevilacqua, M. (2015). Classes of compactly supported covariance functions for multivariate random fieldsStochastic environmental research and risk assessment29(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 Analysis133, 251-265.
  7. Ruiz-Medina, M. D., & Porcu, E. (2015). Equivalence of Gaussian measures of multivariate random fieldsStochastic 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 estimationStochastic environmental research and risk assessment29(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 Mechanics141(7), 04015002.
  10. Kleiber, W., & Porcu, E. (2015). Nonstationary matrix covariances: compact support, long range dependence and quasi-arithmetic constructionsStochastic environmental research and risk assessment29(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 Systems3(1), 27-41.