Papers

STAT ROSA PRISTINA NOMINE, NOMINA NUDA TENEMUS.

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Publications in Peer Refereed Journals (ISI: Statistics & Probability or Mathematics)

  1. Fasso, A., Esposito, A., Porcu, E., Reverberi, A. P. and Veglio, F. (2003). Statistical sensitivity analysis of packed column reactors for contaminated wastewater. Environmetrics , 14, 8.
  2. Porcu, E., Gregori, P. and Mateu, J. (2006). Nonseparable stationary anisotropic space-time covariance functions. Stochastic Environmental Research and Risk Assessment, 21, 113-122.
  3. Porcu, E., Mateu, J., Zini, A. and Pini, R. (2006). The Dagum family for spatio-temporal modelling. Advances in Applied Probability, 37, 1-17.
  4. Yu, K., Mateu, J. and Porcu, E. (2007). A kernel-based method for nonparametric estimation of variograms. Statistica Neerlandica, 61 (2), 173-197.
  1. Porcu, E., Mateu, J., Zini, A. and Pini, R. (2007). Modelling spatio-temporal data: a new variogram and covariance structure proposal. Statistics and Probability Letters, 77, 83-89.
  2. Porcu, E., Mateu, J. and Bevilacqua, M. (2007). Covariance functions which are stationary or nonsta- tionary in space and stationary in time. Statistica Neerlandica, 61 (3), 358-382
  3. Porcu, E. and Mateu, J. (2007). Mixture-based modeling for space-time data. Environmetrics, 18, 285-302
  4. Mateu, J., Juan, P. and Porcu, E. (2007). Geostatistical analysis through spectral techniques: some words of caution. Communications in Statistics: Computation and Simulation, 36 (5), 1035-1051.
  5. Porcu, E., Nicolis, O. and Mateu, J. (2007). A note on decoupling of local and global behaviour for the Dagum random field. Probabilistic Engineering Mechanics, 22 (4), 320-329.
  6. Porcu, E., Gregori, P. and Mateu, J. (2007). La descente et la mont ́ee ́etendues: the spatially d- anisotropic and the spatiotemporal case. Stochastic Environmental Research and Risk Assessment, 21 (6), 683-693.
  7. Mateu, J., Porcu, E., Christakos, G. and Bevilacqua, M. (2007). Fitting negative spatial covariances to geothermal field temperatures in Nea Kessani (Greece). Environmetrics, 18, 759-773.
  8. Mateu, J., Lorenzo, G. and Porcu, E. (2007). Detecting features in spatial point processes with clutter via local indicators of spatial association. Journal of Computational and Graphical Statistics, 16 (4), 968-990.
  9. Gregori, P., Porcu, E., Mateu, J. and Sasvari, Z. (2008). On potentially negative space time covariances obtained as sum of products of marginal ones. Annals of the Institute of Statistical Mathematics, 60, 865-882.
  10. Mateu, J., Porcu, E. and Gregori, P. (2008). Recent advances to model anisotropic space-time data. Statistical Methods & Applications, 17, 209-223.
  11. Porcu, E., Mateu, J. and Saura, F. (2008). New classes of covariance and spectral density functions for spatio-temporal modelling. Stochastic Environmental Research and Risk Assessment, 22 (1), 65-79.
  12. Debon, A., Montes, F., Mateu, J., Porcu, E. and Bevilacqua, M. (2008). Modelling residuals depen- dence in dynamic life tables: a geostatistical approach. Computational Statistics and Data Analysis, 52, 3128-3147.
  13. Berg, C., Mateu, J. and Porcu, E. (2008). The Dagum family of isotropic correlation functions. Bernoulli, 14 (4), 1134-1149.
  14. Porcu, E., Gregori, P. and Mateu, J. (2009). Archimedean spectral densities for nonstationary space- time Geostatistics. Statistica Sinica, 19 (1), 273-286.
  15. Porcu, E., Crujeiras, R., Mateu, J. and Gonzalez-Manteiga, W. (2009). Spatial and spatio-temporal dependence of the periodogram for regularly spaced data. Theory of Probability and its Applications 53 (2), 349–356.
  16. Bevilacqua, M., Mateu, J., Porcu, E., Zhang, H. and Zini, A. (2010). Weighted composite likelihood- based tests for space-time separability of covariance functions. Statistics and Computing, 20 (3), 283-293. DOI: 10.1007/s11222 − 009 − 9121 − 3.
  17. Porcu, E., Matkowski, J. and Mateu, J. (2010). Functional equations related to a problem of reducibility of non-stationary correlation functions to stationary ones. Stochastic Environmental Research and Risk Assessment 24 (5), 599-610.
  1. Porcu, E., Mateu, J. and Comas, C. (2010). Continuous spatio-temporal dynamics of stochastic pro- cesses. Communications in Statistics: Theory and Methods 39, 3472-3484.
  2. Martinez, F., Mateu, J., Montes, F. and Porcu, E. (2010). Mortality risk assessment through stationary space-time covariance functions. Stochastic Environmental Research and Risk Assessment 24, 519–526.
  3. Lorenzo, G., Mateu, J. and Porcu, E. (2010). Features detection in spatial point processes via cluster and MDS techniques.Environmetrics 21, 400-414.
  4. Porcu, E., Mateu, J. and Christakos, G. (2010). Quasi-arithmetic means of covariance functions with potential applications to space-time data. Journal of Multivariate Analysis. 100 (8), 1830-1844.
  5. Mateu, J., Montes, F. and Porcu, E. (2010). Spatio-temporal stochastic modelling: environmental and health processes. Environmetrics, 21, 221-223.
  6. Porcu, E. and Schilling, R. (2011). From Schoenberg to Pick-Nevanlinna: towards a complete picture of the variogram class. Bernoulli, 17 (1), 441–455.
  7. Ruiz Medina, M.D., Porcu, E. and Fernandez Pascual, R. (2011) The Dagum and auxiliary covariance families: towards reconciling two-parameter models that separate fractal dimension and Hurst effect. Probabilistic Engineering Mechanics, 26, 259–268
  8. Zastavnyi, V.P. and Porcu, E. (2011). Compactly supported space-time covariance functions. Bernoulli, 17 (1), 456–465.
  9. Ober, U., Erbe, M. Long, N., Porcu, E., Martin Schlather, M., Simianer, H. (2011). Predicting Genetic Values: a Kernel-Based Best Linear Unbiased Prediction with Genomic Data. Genetics, 188(3), 695- 708.
  10. Papaspiliopoulos, O. and Porcu, E. (2011). Comment on the paper by Lindgren, Rue and Lindstrom. Journal of the Royal Statistical Society, B. 73(4), 423-498.
  11. Porcu, E., Giraldo, R. and Alonso, C. (2012). Discussion to the paper: Vignettes and health systems responsiveness in cross-country comparative analyses. Journal of the Royal Statistical Society, A. 175.
  12. Porcu, E., Alonso, C. and Zini, A. (2012). Discussion to the paper: Statistical methods for healthcare regulation: rating, screening and surveillance, by Spiegelhalter, D., Sherlaw-Johnson, C., Bardsley, M., Blunt, I., Wood, C. & Grigg, O. Journal of the Royal Statistical Society, A, 175.
  13. Porcu, E. and Stein, M.L. (2012). On some local, global and regularity behaviour of some classes of covariance functions. Advances and Challenges in Space-Time Modelling of Natural Events, E. Porcu, J.M. Montero and M. Schlather (Eds). Springer Verlag, Vol. 207, 221–239.
  14. Fernandez-Aviles, G., Montero, J.M., Porcu, E. and Schlather, M. (2012). Introduction to Space–Time processes for Environmental Sciences. To appear to Advances and Challenges in Space-Time Modelling of Natural Events, E. Porcu, J.M. Montero and M. Schlather (Eds). Springer Verlag, Vol. 207, 1–24.
  15. Porcu, E. and Zastavnyi, V. (2011) Characterization theorems for some classes of covariance functions associated to vector valued random fields. Journal of Multivariate Analysis, 102, 1293-1301
  16. Hristopoulos, D. and Porcu, E. (2012). Discussion to the Paper: Catching up faster by switching sooner: a predictive approach to adaptive estimation with an application to the Akaike information criterion – Bayesian information criterion dilemma by van Erven, Gru ̈nwald, de Rooij. Journal of the Royal Statistical Society, B. 74.
  1. Gonzalez–Manteiga, W. and Porcu, E. (2012). Discussion to the paper: ”Optimum design of exper- iments for statistical inference” by Gilmour and Trinca. Journal of the Royal Statistical Society, A. 61.
  2. Porcu, E., Gregori, P., Mateu, J. and Ostoja-Starzewski, M. (2012). New classes of spectral densities for lattice processes and random fields built from simple univariate marginals. Stochastic Environmental Research and Risk Assessment. 26, 4, 479-490.
  3. Porcu, E., Giraldo, R. and Alonso, C. (2012). Discussion to the paper: Vignettes and health systems responsiveness in cross-country comparative analyses. Journal of the Royal Statistical Society, A. 175, 337-369.
  4. Zini, A. and Porcu, E. (2012). Discussion to the paper: Probabilistic index models, by Thas, O., De Neve, J., Clement, L. & and Ottoy, J-P. Journal of the Royal Statistical Society, B, 74.
  5. Leiva, V. and Porcu, E. (2012). Discussion to the paper ”Experimental designs for identifying causal mechanisms” by K. Imai, D. Tingley and T. Yamamoto. J. R. Statist. Soc. A, pp. 1-27.
  6. Bevilacqua, M., Gaetan, C., Mateu, J. and Porcu, E. (2012) Estimating space and space-time covariance functions for large data sets: a weighted composite likelihood approach. Journal of the American Statistical Association (JASA), 107, 268-280.
  7. Porcu, E., Daley, D.J., Buhmann, M. and Bevilacqua, M. (2013). Radial basis functions for multivariate geostatistics. Stochastic Environmental Research Risk Assessment, 27, 4, 909-922.
  8. Amo, M., Lopez–Fidalgo, J., and Porcu, E. (2013). On some stochastic processes whose covariance is a function of the mean, with an application to compartmental models. Test. .22, issue 1, pages 159-181
  9. Porcu, E. and Schilling, R. (2013). Addendum to ”From Schoenberg to Pick-Nevanlinna: towards a complete picture of the variogram class”. Bernoulli Journal, 19, 2768.
  10. Daley, D.J. and Porcu, E. (2013). Dimension walks through Schoenberg spectral measures. Proceedings of the American Mathematical Society.  Vol. 142, Nº 5, 2014 págs. 1813-1824
  11. Cuevas, F., Porcu, E. and Vallejos. R (2013). Study of Spatial Relationships Between Two Sets of Variables: A Nonparametric Approach. Journal of Nonparametric Statistics, 25, 3, 695-714.
  12. Porcu, E. and Zastavnyi, V.P. (2013). Generalized Askey Functions and their walks through dimensions. Exposithiones Matematicae. Volume 32, Issue 2, 2014, Pages 190–198.
  13. Vallejos, R., Porcu, E., Bevilacqua, M. (2013). Discussion of the paper “How to find an appropriate clustering for mixed type variables with application to socio-economic variables” by Hennig C. and Liao, T. F. Journal of The Royal Statistical Society C, 62(3), 309–369.
  14. Khosravi, M., Leiva, V., Jamalizadeh, M. and Porcu, E. (2013). On a nonlinear Birnbaum–Saunders model based on a bivariate construction and its characteristics. Communications in Statistics. Theory & Methods. To appear.
  15. López, F. and Porcu, E. (2013). On the paper by Alonso et al. Biometrical Journal. Forthcoming.
  16. Crudu, F., Porcu, E. and Bevilacqua, M. (2013). A Note on the paper by Frick, Munk and Sieling.  Journal of the Royal Statistical Society, B,76(2). 
  17. Ostoja-Starzewski, M., Shen, L. and Porcu, E. (2013).  Responses of first-order dynamical systems to Matérn, Cauchy or Dagum noises. Mathematical Mechanics Complex Systems (MEMOCS). Accepted for Publication.
  18. Guillot, G. Schilling, R. Porcu, E. and Bevilacqua, M. (2014). Valid covariance models for the analysis of geographical genetic variation. Methods in Ecology and Evolution, 5, 4, 329-335.
  19. Fassó, A. and Porcu, E. (2014). Space-Time Processes and Latent Variables. Stochastic Environmental Research Risk Assessment. To Appear.
  20. Gregori, Porcu and Mateu (2014). Gaussian Random Fields: Escaping from Isotropic, Stationary and non negative covariance functions. Image Analysis and Stereology, 33, 1, 75-81.
  21. Kleiber, W. and Porcu, E. (2014).  Nonstationary matrix covariances: Compact support, long range dependence and adapted spectra. Stochastic Env. Research Risk Assessment. In press.
  22. Lagos, B., Ferreira, G. and Porcu, E. (2014). Modified Maximum Likelihood Estimation in Autoregressive Processes with Generalized Exponential Innovations. Open Journal of Statistics, 4, 620–629. 
  23. Bevilacqua, M., Crudu, F. and Porcu, E. (2015).

    Combining Euclidean and composite likelihood for binary spatial data estimation. Stochastic Environmental Research Risk Assessment. 29, 335-346.

  24. L. Shen, M. Ostoja-Starzewski and E. Porcu (2014), “Elastic rods and shear beams with random field properties under random field loads: fractal and Hurst effects,” ASCE Journal of Engineering Mechanics, in press.
  25. L. Shen, M. Ostoja-Starzewski and E. Porcu (2014), “Bernoulli-Euler beams with random field properties under random field forcings: fractal and Hurst effects,” accepted, Arch. Appl. Mech. 84, 1595-1626.
  26. Hristopoulos, D. and Porcu (2014). Vector Spartan Spatial Random Field Models. Probabilistic Engineering Mechanics, 37, 84–92.
  27. Ruiz-Medina, M.D. and Porcu, E. (2015). Equivalence of Gaussian Measures for Multivariate Gaussian random fields. Stochastic Environmental Research Risk Assessment, 29, 325-334.
  28. Alonso-Malaver, C. Porcu, E. and Giraldo, El Moncho (2015). Multivariate and Multiradial Schoenberg Measures with their Dimension Walk. Journal of Multivariate Analysis, 133, 251-265.
  29. Daley, D.J., Porcu, E. and Bevilacqua, M. (2015). Classes of compactly supported covariance functions for multivariate random fields. Stochastic Environmental Research Risk Assessment, 29, 4, 1249-1263.
  30. Salazar, E., C., Porcu, E. and Giraldo, El Moncho (2015). Spatial Prediction for Infinite-Dimensional Compositional Data. Stochastic Environmental Research Risk Assessment, 29, 7, 1737-1749.
  31. Castro, D. and Porcu, E. (2015). Discussion on the paper by Gerber and Chopin. Journal of the Royal Statistical Society, B. Forthcoming.
  32. Bevilacqua, M., Hering, A.S. and Porcu, E. (2015). On the flexibility of multivariate covariance models. Comment paper on the paper by Genton and Kleiber. Statistical Science, 30, 2, 165-169.
  33. Allard, D. Porcu, E. and Senoussi, R. (2016). Anisotropy Models for Spatial Data.  Mathematical Geosciences, 48, 3, 305-328.
  34. Ostoja-Starzewski, M., Shen, L. and Porcu, E. (2016). Harmonic oscillator driven by random processes having fractal and Hurst effects. Acta Mechanica, 226, 11, 3653-3672.
  35. Shamshirband, Mohammadi, Tong, Petkovic, Porcu, Mostafaeipour, Sudheer, Ahmad Sedaghat. (2016). Application of extreme learning machine for estimation of wind speed distribution. Climate Dynamics, 216, 46, 5, 1893-1907.
  36. Hering, A.S., Bevilacqua, M. and Porcu, E. (2016). Comment on the 2016   paper “Statistical modelling of citation exchange between statistics journals” by  C.~Varin, M.~Cattelan, and D.~Firth, \emph{J. R. Statist. Soc. A}, 179: 1–33.
  37. Porcu, E., Bevilacqua, M. and Genton, M. (2015). Spatio-Temporal Covariance and Cross-Covariance Functions of the Great Circle Distance on a Sphere. Journal of the American Statistical Association. Forthcoming.
  38. M. Bevilacqua, A. Fassò, C. Gaetan, E. Porcu and D. Velandia (2016). Covariance tapering for multivariate Gaussian random fields estimation. Statistical Methods and Applications, 25, 21-37.
  39. Emery, X., Arroyo, D. and Porcu, E. (2015).

    An improved spectral turning-bands algorithm for simulating stationary vector Gaussian random fields. Stochastic Env. Research Risk Assessment. Accepted.

  40. Berg, C. and Porcu, E. (2016). From Schoenberg coefficients to Schoenberg functions. Constructive Approximation. Accepted.
  41. Alonso-Malaver, C, Porcu, E. and Giraldo, El Moncho (2016). Multivariate Versions of Walks Through Dimensions and Schoenberg measures. Brazilian Journal of Probability and Statistics. Accepted.
  42. Allard, D., Bourotte, M. and Porcu, E. (2016). A Flexible Class of Non-separable Cross-Covariance Functions for Multivariate Space-Time Data. Spatial Statistics. Accepted.
  43. Alegría, A., Bevilacqua, M. and Porcu, E. (2016). Likelihood-based inference for multivariate space-time wrapped-Gaussian fields. Journal of Statistical Computation and Simulation. Accepted.
  44. Bevilacqua M., Alegria A., Velandia D., Porcu E. (2016) Composite likelihood inference for multivariate Gaussian random fields.    Journal of Agricultural Biological and Environmental Statistics. DOI: 10.1007/s13253-016-0256-3.
  45. Moller, J., Nielsen, M., Porcu, E. and Rubak, E. (2015). Determinantal point process models on the sphere. Bernoulli. Accepted.
  46. Mateu, J. and Porcu, E. (2016). Seismomatics: Space–Time Analysis of Natural or Anthropogenic Catastrophes. JABES. Accepted.
  47. Zastavnyi, V.P. and Porcu, E. (2016). On positive definiteness of some radial functions. Lobatchevkii journal of Mathematics. Accepted.
  48. Nishavala, V. Ostoja-Starzewski, M., Leamy, M. and Porcu, E. (2016). Lamb’s Problem on Random Mass Density Fields with Fractal and Hurst effects. Proc. Royal Society, A. Accepted.
  49. Barca, E., Passarella, G; Bruno, D; Porcu, E. (2015). A novel software application for providing an improved cross-validation of variogram models. Environmental Modelling & Software. Accepted.
  50. Porcu, E., Fassó, A., Barrientos, S. and Catalán, P. (2016). Seismomatics. Stochastic Environmental Research Risk Assessment. Accepted.
  51. Coeurjolly, J.F. and Porcu, E. (2016). Circularly symmetric fractional Brownian motion. Statistics & Probability Letters. Accepted.
  52.  Lagos, B., Porcu, E. and Lara, L. (2017). Discussion to the paper by Gelman and Hering. Journal of the Royal Statistical Society, A. To appear.
  53. Ferreira, G., Mateu, J. and Porcu, E. (2017). Spatio-Temporal Analysis with Short and Long-Memory Dependence: A State-Space Approach. Test. Accepted.

Papers submitted to International Journals.

Note: for technical reasons, I do NOT report submitted papers which are under double blinding process, in order to respect the policy of the Journal.

  1.  Ostoja-Starzewski, M., Shen, L. and Porcu, E. (2013). Shear beams with random field properties under random field forcings with fractal and Hurst effects
  2. Bevilacqua, M., Genton, M., Porcu, E. and Zastavnyi, V. (2014). Adaptive tapering for space-time covariance functions.
  3. Crudu, F. and Porcu, E. (2013). Z estimators and auxiliary information for strong mixing processes. Submitted.
  4. Ferreira, G., Piña, J.N. and Porcu, E. (2013).  On Trend Estimation for Locally Stationary Processes.
  5. Lagos, B., Ferreira, G. and Porcu, E. (2014).  Forecasting Locally Stationary Processes through Bootstrap Techniques.
  6. Ostoja-Starzewski, M., Nishawala, V. and Porcu, E. Effect of mass density spatial randomness on Transient wave propagation -II: multiscale random fields.  Submitted.
  7. Coeurjolly, J.F. and Porcu, E. (2016). Fast and exact simulation of complex-valued stationary Gaussian processes through embedding circulant matrix. Submitted.
  8. Porcu, E., Zastavnyi, V.P. and Bevilacqua, M. (2016).  Buhmann covariance functions, their compact supports, and their smoothness. Submitted.
  9. Bevilacqua, M., Faouzi, T., Furrer, R. and Porcu, E. (2016). Estimation and Prediction using generalized Wendland functions under fixed domain asymptotics. Submitted.
  10. Cuevas, F., Porcu, E. and Bevilacqua, M.(2016). Contours and Dimples for the Gneiting class of space-time covariance functions. Submitted.
  11. Peron, A. and Porcu, E. (2016). Positive definite functions on complex spheres, and their walks through dimensions. Submitted.
  12. Clarke, J., Alegria, A. and Porcu, E. (2016). Regularity properties and simulations of Gaussian random fields on the Sphere cross Time. Submitted.
  13. Alegria, A. and Porcu, E. (2016). The dimple problem related to space-time modeling under the Lagrangian framework. Submitted.
  14. Arafat, A., Porcu, E., Bevilacqua, M. and Mateu, J. (2016). Equivalence and Orthogonality of Gaussian Measures on Spheres. Submitted.
  15. Alegría, A., Caro, S., Bevilacqua, M., Porcu, E. and Clarke, J. (2016).

    Estimating covariance functions of multivariate skew-Gaussian random fields on the sphere. Submitted.

  16. Berg, C., Peron, A. and Porcu, E. (2016). Orthogonal expansions related to compact Gelfand pairs.
  17. Estrade, A., Fariñas, A. and Porcu, E. (2016).  Characterization Theorems for Covariance Functions on the n−Dimensional Sphere Across Time. Submitted.
  18. Alegria, A., Porcu, E., Furrer, R. and Mateu, J. (2017).  Covariance Functions for Multivariate Gaussian Fields evolving temporally over Planet Earth. Submitted.
  19. Berg, C., Peron, A. and Porcu, E. (2017). Schoenberg’s theorem for real and complex Hilbert spheres revisited. Submitted.
  20. Alegria, A. and Porcu, E. (2017). Space-Time Geostatistical Models with both Linear and Seasonal Structures in the Temporal Components. Submitted.
  21. Arafat, A., Gregori, P. and Porcu, E. (2017). GNEITING’S PROBLEMS AND THE CLASS Ψd OF POSITIVE DEFINITE FUNCTIONS OVER HYPERSPHERES. Submitted.
  22. Castruccio, S. and Porcu, E. (2017). A Bridge between Equivalence of Gaussian Measures and SPDE representations. Submitted.
  23. Porcu, E., Alegria, A. and Furrer, R. (2017). Modeling Temporally Evolving and Spatially Globally Dependent Data. Submitted.
  24. Guella, J.C., Menegatto, V. and Porcu, E. (2017). Strictly Positive Definite Multivariate Covariance Functions on Spheres. Submitted.