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09/15/2023
TreeLearn: A Comprehensive Deep Learning Method for Segmenting Individual Trees from Forest Point Clouds
Laser-scanned point clouds of forests make it possible to extract valuab...
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02/14/2023
"Spatial Joint Models through Bayesian Structured Piece-wise Additive Joint Modelling for Longitudinal and Time-to-Event Data"
Joint models for longitudinal and time-to-event data have seen many deve...
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01/27/2023
Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean
Deep neural networks (DNNs) have proven to be highly effective in a vari...
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09/22/2022
Liesel: A Probabilistic Programming Framework for Developing Semi-Parametric Regression Models and Custom Bayesian Inference Algorithms
Liesel is a probabilistic programming framework focusing on but not limi...
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08/22/2022
Multivariate Distributional Stochastic Frontier Models
The primary objective of Stochastic Frontier (SF) Analysis is the deconv...
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07/08/2022
Twitmo: A Twitter Data Topic Modeling and Visualization Package for R
We present Twitmo, a package that provides a broad range of methods to c...
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05/17/2022
Bayesian Discrete Conditional Transformation Models
We propose a novel Bayesian model framework for discrete ordinal and cou...
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04/02/2022
Distributional Gradient Boosting Machines
We present a unified probabilistic gradient boosting framework for regre...
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11/28/2021
Using the Softplus Function to Construct Alternative Link Functions in Generalized Linear Models and Beyond
Response functions linking regression predictors to properties of the re...
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06/07/2021
A multivariate Gaussian random field prior against spatial confounding
Spatial models are used in a variety research areas, such as environment...
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05/18/2021
Flexible Bayesian Modeling of Counts: Constructing Penalized Complexity Priors
Many of the data, particularly in medicine and disease mapping are count...
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01/14/2021
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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12/20/2020
Bayesian Conditional Transformation Models
Recent developments in statistical regression methodology establish flex...
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09/08/2020
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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06/05/2020
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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10/18/2019
Noncrossing structured additive multiple-output Bayesian quantile regression models
Quantile regression models are a powerful tool for studying different po...
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08/02/2019
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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06/07/2019
Multivariate Conditional Transformation Models
Regression models describing the joint distribution of multivariate resp...
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02/27/2019
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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06/25/2018
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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06/10/2018
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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03/15/2018
Conditional Model Selection in Mixed-Effects Models with cAIC4
Model selection in mixed models based on the conditional distribution is...
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11/29/2017
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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10/06/2017
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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09/09/2016
