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Adaptive shrinkage of smooth functional effects towards a predefined functional subspace
In this paper, we propose a new horseshoe-type prior hierarchy for adapt...
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Bayesian Conditional Transformation Models
Recent developments in statistical regression methodology establish flex...
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Beyond unidimensional poverty analysis using distributional copula models for mixed ordered-continuous outcomes
Poverty is a multidimensional concept often comprising a monetary outcom...
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Analytic expressions for the Cumulative Distribution Function of the Composed Error Term in Stochastic Frontier Analysis with Truncated Normal and Exponential Inefficiencies
In the stochastic frontier model, the composed error term consists of th...
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Noncrossing structured additive multiple-output Bayesian quantile regression models
Quantile regression models are a powerful tool for studying different po...
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Generalised Joint Regression for Count Data with a Focus on Modelling Football Matches
We propose a versatile joint regression framework for count responses. T...
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Multivariate Conditional Transformation Models
Regression models describing the joint distribution of multivariate resp...
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Bayesian Effect Selection in Structured Additive Distributional Regression Models
We propose a novel spike and slab prior specification with scaled beta p...
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Generalized additive models for location, scale and shape for program evaluation: A guide to practice
This paper introduces generalized additive models for location, scale an...
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Lost in translation: On the impact of data coding on penalized regression with interactions
Penalized regression approaches are standard tools in quantitative genet...
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Conditional Model Selection in Mixed-Effects Models with cAIC4
Model selection in mixed models based on the conditional distribution is...
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Bayesian Measurement Error Correction in Structured Additive Distributional Regression with an Application to the Analysis of Sensor Data on Soil-Plant Variability
The flexibility of the Bayesian approach to account for covariates with ...
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Gradient boosting in Markov-switching generalized additive models for location, scale and shape
We propose a novel class of flexible latent-state time series regression...
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Boosting Joint Models for Longitudinal and Time-to-Event Data
Joint Models for longitudinal and time-to-event data have gained a lot o...
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