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Bachoc, F.; Porcu, E.; Bevilacqua, M.; Furrer, R.; Faouzi, T. Asymptotically equivalent prediction in multivariate geostatistics 2022 Bernoulli 28 2518-2545 details   doi
Bevilacqua, M.; Caamano-Carrillo, C.; Arellano-Valle, R.B.; Gomez, C. A class of random fields with two-piece marginal distributions for modeling point-referenced data with spatial outliers 2022 Test 31 644-674 details   doi
Bevilacqua, M.; Camano-Carrillo, C.; Porcu, E. Unifying compactly supported and Matern covariance functions in spatial statistics 2022 Journal of Multivariate Analysis 189 104949 details   doi
Blasi, F.; Caamano-Carrillo, C.; Bevilacqua, M.; Furrer, R. A selective view of climatological data and likelihood estimation 2022 Spatial Statistics 50 100596 details   doi
Caamaño-Carrillo, C.; Bevilacqua, M.; López, C.; Morales-Oñate, V. Nearest neighbors weighted composite likelihood based on pairs for (non-)Gaussian massive spatial data with an application to Tukey-hh random fields estimation 2024 Computational Statistics & Data Analysis 191 107887 details   doi
Faouzi, T.; Porcu, E.; Bevilacqua, M. SPACE-TIME ESTIMATION AND PREDICTION UNDER FIXED-DOMAIN ASYMPTOTICS WITH COMPACTLY SUPPORTED COVARIANCE FUNCTIONS 2022 Statistica Sinica 32 1187-1203 details   doi
Faouzi, T.; Porcu, E.; Kondrashuk, I.; Bevilacqua, M. Convergence arguments to bridge cauchy and matern covariance functions 2023 Statistical Papers Early Access details   doi
Morales-Navarrete, D.; Bevilacqua, M.; Caamano-Carrillo, C.; Castro, L.M. Modeling Point Referenced Spatial Count Data: A Poisson Process Approach 2023 Journal of the American Statistical Association Early Access details   doi
Morales-Onate, V.; Crudu, F.; Bevilacqua, M. Blockwise Euclidean likelihood for spatio-temporal covariance models 2021 Econometrics and Statistics 20 176-201 details   doi
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