The tipsae package implements a set of small area estimation tools for mapping proportions and indicators defined on the unit interval. It provides for small area models defined at area level, including the classical beta regression, zero- and/or one-inflated beta and flexible beta ones, possibly accounting for spatial and/or temporal dependency structures. The models, developed within a Bayesian framework, are estimated through Stan language, allowing fast estimation and customized parallel computing. The additional features of the tipsae package, such as diagnostics, visualization and exporting functions as well as variance smoothing and benchmarking functions, improve the user experience through the entire process of estimation, validation and outcome presentation. A shiny application with a user-friendly interface further eases the implementation of Bayesian models for small area analysis.
De Nicolò, S., Gardini, A. (2024). The R Package tipsae: Tools for Mapping Proportions and Indicators on the Unit Interval. JOURNAL OF STATISTICAL SOFTWARE, 108(1), 1-36 [10.18637/jss.v108.i01].
The R Package tipsae: Tools for Mapping Proportions and Indicators on the Unit Interval
De Nicolò, S.
;Gardini, A.
2024
Abstract
The tipsae package implements a set of small area estimation tools for mapping proportions and indicators defined on the unit interval. It provides for small area models defined at area level, including the classical beta regression, zero- and/or one-inflated beta and flexible beta ones, possibly accounting for spatial and/or temporal dependency structures. The models, developed within a Bayesian framework, are estimated through Stan language, allowing fast estimation and customized parallel computing. The additional features of the tipsae package, such as diagnostics, visualization and exporting functions as well as variance smoothing and benchmarking functions, improve the user experience through the entire process of estimation, validation and outcome presentation. A shiny application with a user-friendly interface further eases the implementation of Bayesian models for small area analysis.File | Dimensione | Formato | |
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