Multilevel time series modelling of mobility trends in the Netherlands for small domains
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DOI: 10.1111/rssa.12700
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- Carter, C.K. & Kohn, R., "undated". "Markov Chain Monte Carlo in Conditionally Gaussian State Space Models," Statistics Working Paper _003, Australian Graduate School of Management.
- Oksana Bollineni‐Balabay & Jan van den Brakel & Franz Palm & Harm Jan Boonstra, 2017. "Multilevel hierarchical Bayesian versus state space approach in time series small area estimation: the Dutch Travel Survey," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(4), pages 1281-1308, October.
- Stefan Lang & Eva-Maria Pronk & Ludwig Fahrmeir, 2002. "Function estimation with locally adaptive dynamic models," Computational Statistics, Springer, vol. 17(4), pages 479-499, December.
- Enrico Fabrizi & Maria Rosaria Ferrante & Carlo Trivisano, 2018. "Bayesian small area estimation for skewed business survey variables," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(4), pages 861-879, August.
- Jan Pablo Burgard & María Dolores Esteban & Domingo Morales & Agustín Pérez, 2020. "A Fay–Herriot model when auxiliary variables are measured with error," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 166-195, March.
- Shonosuke Sugasawa & Hiromasa Tamae & Tatsuya Kubokawa, 2017. "Bayesian Estimators for Small Area Models Shrinking Both Means and Variances," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(1), pages 150-167, March.
- Datta, G. S. & Lahiri, P., 1995. "Robust Hierarchical Bayes Estimation of Small Area Characteristics in the Presence of Covariates and Outliers," Journal of Multivariate Analysis, Elsevier, vol. 54(2), pages 310-328, August.
- Carlos M. Carvalho & Nicholas G. Polson & James G. Scott, 2010. "The horseshoe estimator for sparse signals," Biometrika, Biometrika Trust, vol. 97(2), pages 465-480.
- David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
- Xueying Tang & Malay Ghosh & Neung Soo Ha & Joseph Sedransk, 2018. "Modeling Random Effects Using Global–Local Shrinkage Priors in Small Area Estimation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(524), pages 1476-1489, October.
- Lynn M. R. Ybarra & Sharon L. Lohr, 2008. "Small area estimation when auxiliary information is measured with error," Biometrika, Biometrika Trust, vol. 95(4), pages 919-931.
- Serena Arima & Gauri S. Datta & Brunero Liseo, 2015. "Bayesian Estimators for Small Area Models when Auxiliary Information is Measured with Error," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 518-529, June.
- O’Malley, A. James & Zaslavsky, Alan M., 2008. "Domain-Level Covariance Analysis for Multilevel Survey Data With Structured Nonresponse," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1405-1418.
- A. Brezger & L. Fahrmeir & A. Hennerfeind, 2007. "Adaptive Gaussian Markov random fields with applications in human brain mapping," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(3), pages 327-345, May.
- Gauri Sankar Datta & Abhyuday Mandal, 2015. "Small Area Estimation With Uncertain Random Effects," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1735-1744, December.
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- Gagnon, Philippe & Hayashi, Yoshiko, 2023. "Theoretical properties of Bayesian Student-t linear regression," Statistics & Probability Letters, Elsevier, vol. 193(C).
- Bernard Baffour & Sumonkanti Das & Mu Li & Alice Richardson, 2024. "The Utility of Socioeconomic and Remoteness Indicators in Understanding the Geographical Variation in the Regional Prevalence of Early Childhood Vulnerability in Australia," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 17(4), pages 1791-1827, August.
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