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Communications in Statistics - Theory and Methods Volume 40, 2011 - Issue 24
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Original Articles

Strict Positive Definiteness of a Product of Covariance Functions

S. De Iaco Dipartimento di Scienze Economiche e Matematico-Statistiche, Università del Salento, Lecce, ItaliaCorrespondence[email protected]
,
D. E. Myers Department of Mathematics, University of Arizona, Tucson, Arizona, USA
&
D. Posa Dipartimento di Scienze Economiche e Matematico-Statistiche, Università del Salento, Lecce, Italia
Pages 4400-4408 | Received 23 Mar 2010, Accepted 27 Jul 2010, Published online: 10 Nov 2011

Citations (17)

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Donato Posa. (2023) Positive definite functions, stationary covariance functions, and Bochner’s theorem: Some results and a critical overview. Communications in Statistics - Theory and Methods 0:0, pages 1-17.
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Articles from other publishers (16)

D. Posa. (2023) Special classes of isotropic covariance functions. Stochastic Environmental Research and Risk Assessment 37:4, pages 1615-1633.
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Donato Posa. (2021) Models for the difference of continuous covariance functions. Stochastic Environmental Research and Risk Assessment 35:7, pages 1369-1386.
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Donato Posa. (2020) Parametric families for complex valued covariance functions: Some results, an overview and critical aspects. Spatial Statistics 39, pages 100473.
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S. De Iaco, D. Posa, C. Cappello & S. Maggio. (2019) Isotropy, symmetry, separability and strict positive definiteness for covariance functions: A critical review. Spatial Statistics 29, pages 89-108.
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Jean Carlo Guella, Valdir Antonio Menegatto & Emilio Porcu. (2018) Strictly positive definite multivariate covariance functions on spheres. Journal of Multivariate Analysis 166, pages 150-159.
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S. De Iaco, M. Palma & D. Posa. (2016) A general procedure for selecting a class of fully symmetric space-time covariance functions. Environmetrics 27:4, pages 212-224.
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T.G. Orton, M.J. Pringle & T.F.A. Bishop. (2016) A one-step approach for modelling and mapping soil properties based on profile data sampled over varying depth intervals. Geoderma 262, pages 174-186.
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S. De Iaco, M. Palma & D. Posa. (2015) Spatio-temporal geostatistical modeling for French fertility predictions. Spatial Statistics 14, pages 546-562.
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Zhaocheng Zeng, Liping Lei, Shanshan Hou, Fei Ru, Xianhua Guan & Bing Zhang. (2014) A Regional Gap-Filling Method Based on Spatiotemporal Variogram Model of <inline-formula> <tex-math notation="TeX">$\hbox{CO}_{2}$</tex-math></inline-formula> Columns. IEEE Transactions on Geoscience and Remote Sensing 52:6, pages 3594-3603.
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S. De Iaco, D. Posa & D.E. Myers. (2013) Characteristics of some classes of space–time covariance functions. Journal of Statistical Planning and Inference 143:11, pages 2002-2015.
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S. De Iaco, M. Palma & D. Posa. (2012) Prediction of particle pollution through spatio-temporal multivariate geostatistical analysis: spatial special issue. AStA Advances in Statistical Analysis 97:2, pages 133-150.
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S. De Iaco, D. E. Myers, M. Palma & D. Posa. (2012) Using Simultaneous Diagonalization to Identify a Space–Time Linear Coregionalization Model. Mathematical Geosciences 45:1, pages 69-86.
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Sabrina Maggio, Claudia Cappello & Daniela Pellegrino. 2013. Statistical Methods for Spatial Planning and Monitoring. Statistical Methods for Spatial Planning and Monitoring 77 92 .
Sandra De Iaco, Monica Palma & Donato Posa. 2013. Statistical Methods for Spatial Planning and Monitoring. Statistical Methods for Spatial Planning and Monitoring 47 75 .
S. De Iaco & D. Posa. (2012) Predicting spatio-temporal random fields: Some computational aspects. Computers & Geosciences 41, pages 12-24.
Crossref
S. De Iaco, S. Maggio, M. Palma & D. Posa. (2012) Towards an automatic procedure for modeling multivariate space–time data. Computers & Geosciences 41, pages 1-11.
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