Unemployment estimation: Spatial point referenced methods and models

Spatial Statistics - Tập 41 - Trang 100345 - 2021
Soraia Pereira1, K.F. Turkman1, Luís Correia2, Håvard Rue3
1CEAUL-Faculdade de Ciências, University of Lisbon, Portugal
2Instituto Nacional de Estatística, Lisboa, Portugal
3King Abdullah University of Science and Technology, Saudi Arabia

Tài liệu tham khảo

Baddeley, 2016 Banerjee, 2004 Da-Silva, 2016, Hierarchical dynamic beta model, REVSTAT, 14, 49 Diggle, 2010, Geostatistical inference under preferential sampling, Appl. Statist., 59, 191 Fay, 1979, Estimates of income for small places: an application of James–Stein procedures to census data, J. Amer. Statist. Assoc., 74, 269, 10.1080/01621459.1979.10482505 Fuglstad, 2017 Horvitz, 1952, A generalization of sampling without replacement from a finite universe, J. Amer. Statist. Assoc., 47, 663, 10.1080/01621459.1952.10483446 Illian, 2008 Illian, 2012, A toolbox for fitting complex spatial point process models using integrated nested laplace approximation (inla), Ann. Appl. Stat., 6, 1499, 10.1214/11-AOAS530 Illian, 2012, Using INLA to fit a complex point process model with temporally varying effects – a case study, J. Environ. Stat., 3 2016 Lindgren, 2011, An explicit link between Gaussian fields and Gaussian Markov random fields: the SPDE approach (with discussion), J. R. Stat. Soc. Ser. B, 73, 423, 10.1111/j.1467-9868.2011.00777.x Lopez-Vizcaino, 2015, Small area estimation of labour force indicators under a multinomial model with correlated time and area effects, J. R. Stat. Soc. Ser. A, 178, 535, 10.1111/rssa.12085 Marhuenda, 2013, Small area estimation with spatio-temporal Fay–Herriot models, Comput. Statist. Data Anal., 58, 308, 10.1016/j.csda.2012.09.002 Martins, 2013, Bayesian computing with INLA: New features, Comput. Statist. Data Anal., 67, 68, 10.1016/j.csda.2013.04.014 Molina, 2007, Small area estimates of labour force participation under a multinomial logit mixed model, J.R. Statist. Soc. A, 170, 975, 10.1111/j.1467-985X.2007.00493.x Moller, 2004 Nadaraya, 1964, On estimating regression, Theory Probab. Appl., 9, 157, 10.1137/1109020 Nadaraya, 1989, vol. 20 Pereira, 2018, Spatio-temporal analysis of regional unemployment rates: A comparison of model based approaches, REVSTAT, 16, 515 Rao, 2015 Roos, 2015, Sensitivity analysis for bayesian hierarchical models, Bayesian Anal., 10, 321, 10.1214/14-BA909 Rue, 2009, Approximate Bayesian inference for latent Gaussian models using integrated nested Laplace approximations (with discussion), J. R. Stat. Soc. Ser. B Stat. Methodol., 71, 319, 10.1111/j.1467-9868.2008.00700.x Rue, 2017, Bayesian computing with INLA: A review, Annu. Rev. Stat. Appl., 4, 395, 10.1146/annurev-statistics-060116-054045 Simpson, 2017, Penalising model component complexity: A principled, practical approach to constructing priors (with discussion), Statist. Sci., 32, 1, 10.1214/16-STS576 Spiegelhalter, 2002, Bayesian measures of model complexity and fit (with discussion), J. R. Stat. Soc. Ser. B, 64, 583, 10.1111/1467-9868.00353 Watanabe, 2010, Asymptotic equivalence of Bayes cross validation and widely applicable information criterion in singular learning theory., J. Mach. Learn. Res., 11, 3571 Watson, 1964, Smooth regression analysis, Sankhya Ser. A, 26, 359 You, 2006, Small area estimation using area level models and estimated sampling variances, Surv. Methodol., 32, 97 You, 2011, Hierarchical Bayes small area estimation under a spatial model with application to health survey data, Surv. Methodol., 37, 25 Yuan, 2017, Point process models for spatio-temporal distance sampling data from a large-scale survey of blue whales, Ann. Appl. Stat., 11, 2270, 10.1214/17-AOAS1078