Liesel is a new probabilistic programming framework developed with the aim of supporting research on Bayesian inference based on Markov chain Monte Carlo (MCMC) simulations in general and semi-parametric regression specifications in particular.
Computation
Summary: ipd is an open-source R software package for the downstream modeling of an outcome and its associated features where a potentially sizable portion of the outcome data has been imputed by an artificial intelligence or machine learning (AI/ML) prediction algorithm.
Methodology Computation
To uncover the statistical structures of such data, we propose Functional Singular Value Decomposition (FSVD), a unified framework encompassing various tasks for the analysis of functional data with potential heterogeneity.
Methodology Statistics Theory Applications Computation Statistics Theory
There is a tension between robustness and efficiency when designing Markov chain Monte Carlo (MCMC) sampling algorithms.
Computation Methodology
The rapid development of modern technology facilitates the appearance of numerous unprecedented complex data which do not satisfy the axioms of Euclidean geometry, while most of the statistical hypothesis tests are available in Euclidean or Hilbert spaces.
Computation
Statistical applications in sports have long centered on how to best separate signal (e. g. team talent) from random noise.
Applications
From the outset, we postulate a data-generating model which additively decomposes data into a finite element, a model misspecification and a noise component.
Methodology Numerical Analysis Numerical Analysis
We develop a Bayesian median autoregressive (BayesMAR) model for time series forecasting.
Applications Econometrics Methodology
We present the R-package mgm for the estimation of k-order Mixed Graphical Models (MGMs) and mixed Vector Autoregressive (mVAR) models in high-dimensional data.
Applications
Finally, we developed the free R-package bootnet that allows for estimating psychological networks in a generalized framework in addition to the proposed bootstrap methods.
Applications Methodology