activity
20132022
most citedPenalized Likelihood and Bayesian Function Selection in Regression Models

3 citations · 13 across the 10 of their papers we have counts for

collaborators

13 papers

stat.ME20213 cited

A multivariate Gaussian random field prior against spatial confounding

Isa Marques, Thomas Kneib, Nadja Klein

Spatial models are used in a variety research areas, such as environmental sciences, epidemiology, or physics. A common phenomenon in many spatial regression models is spatial conf…

stat.ME20212 cited

Flexible Bayesian Modeling of Counts: Constructing Penalized Complexity Priors

Mahsa Nadifar, Hossein Baghishani, Thomas Kneib +1

Many of the data, particularly in medicine and disease mapping are count. Indeed, the under or overdispersion problem in count data distrusts the performance of the classical Poiss…

stat.ME20211 cited

Adaptive shrinkage of smooth functional effects towards a predefined functional subspace

Paul Wiemann, Thomas Kneib

In this paper, we propose a new horseshoe-type prior hierarchy for adaptively shrinking spline-based functional effects towards a predefined vector space of parametric functions. I…

stat.ME2020

Beyond unidimensional poverty analysis using distributional copula models for mixed ordered-continuous outcomes

Maike Hohberg, Francesco Donat, Giampiero Marra +1

Poverty is a multidimensional concept often comprising a monetary outcome and other welfare dimensions such as education, subjective well-being or health, that are measured on an o…

stat.ME20202 cited

Analytic expressions for the Cumulative Distribution Function of the Composed Error Term in Stochastic Frontier Analysis with Truncated Normal and Exponential Inefficiencies

Rouven Schmidt, Thomas Kneib

In the stochastic frontier model, the composed error term consists of the measurement error and the inefficiency term. A general assumption is that the inefficiency term follows a…

stat.ME2019

Noncrossing structured additive multiple-output Bayesian quantile regression models

Bruno Santos, Thomas Kneib

Quantile regression models are a powerful tool for studying different points of the conditional distribution of univariate response variables. Their multivariate counterpart extens…