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On the Effects of Spatial Confounding in Hierarchical Models

Nobre, Widemberg S.; Schmidt, Alexandra Mello; Pereira, … - In: International Statistical Review 89 (2020) 2, pp. 302-322

Persistent link: https://www.econbiz.de/10012409298

Identifying deprived "slum" neighbourhoods in the Greater Accra Metropolitan Area of Ghana using census and remote sensing data

MacTavish, Robert; Bixby, Honor; Cavanaugh, Alicia; … - In: World development : the multi-disciplinary … 167 (2023), pp. 1-10

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Bayesian factor model shrinkage for linear IV regression with many instruments

Hahn, P. Richard; He, Jingyu; Lopes, Hedibert Freitas - In: Journal of business & economic statistics : JBES ; a … 36 (2018) 2, pp. 278-287

Persistent link: https://www.econbiz.de/10011894982

Particle learning for fat-tailed distributions

Lopes, Hedibert Freitas; Polson, Nicholas G. - In: Econometric reviews 35 (2016) 8/10, pp. 1666-1691

Persistent link: https://www.econbiz.de/10011592384

Scalable semiparametric inference for the means of heavy-tailed distributions

Lopes, Hedibert Freitas; Taddy, Matthew; Gardner, Matthew - 2019

Persistent link: https://www.econbiz.de/10012244174

Walk on the wild side : temporarily unstable paths and multiplicative sunspots

Ascari, Guido; Bonomolo, Paolo; Lopes, Hedibert Freitas - In: The American economic review 109 (2019) 5, pp. 1805-1842

Persistent link: https://www.econbiz.de/10012013577

Particle learning for Bayesian semi-parametric stochastic volatility model

Virbickaitė, Audronė; Lopes, Hedibert Freitas; … - In: Econometric reviews 38 (2019) 9, pp. 1007-1023

Persistent link: https://www.econbiz.de/10012181379

Parsimony inducing priors for large scale state-space models

Lopes, Hedibert Freitas; McCulloch, Robert E.; Tsay, Ruey S. - In: Journal of econometrics 230 (2022) 1, pp. 39-61

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An adaptive resampling scheme for cycle estimation

Schmidt, Alexandra Mello; Gamerman, Dani; Moreira, Ajax - In: Journal of Applied Statistics 26 (1999) 5, pp. 619-641

Bayesian dynamic linear models (DLMs) are useful in time series modelling, because of the flexibility that they off er for obtaining a good forecast. They are based on a decomposition of the relevant factors which explain the behaviour of the series through a series of state parameters....

Persistent link: https://www.econbiz.de/10005458414

Bayesian Meta-analysis for Longitudinal Data Models Using Multivariate Mixture Priors

Lopes, Hedibert Freitas; Müller, Peter; Rosner, Gary L. - In: Biometrics 59 (2003) 1, pp. 66-75

Persistent link: https://www.econbiz.de/10011036209