Latest Research
Weighting methods for truncation by death in cluster-randomized trials
However, the majority of methods for estimating SACE have been developed in the context of individually-randomized trials.
Methodology Applications
Bayesian Networks for Variational System Identification
dimasad/visid
•
•
This paper details how the Bayesian-network structure of the posterior distribution of state-space models can be exploited to build improved parameterizations for system identification using variational inference.
Applications
General Bayesian inference for causal effects using covariate balancing procedure
In observational studies, the propensity score plays a central role in estimating causal effects of interest.
Methodology
sfislands: An R Package for Accommodating Islands and Disjoint Zones in Areal Spatial Modelling
Fitting areal models which use a spatial weights matrix to represent relationships between geographical units can be a cumbersome task, particularly when these units are not well-behaved.
Methodology Computation
Two-stage Spatial Regression Models for Spatial Confounding
Public health data are often spatially dependent, but standard spatial regression methods can suffer from bias and invalid inference when the independent variable is associated with spatially-correlated residuals.
Methodology
Unraveling stochastic fundamental diagrams considering empirical knowledge: modeling, limitation and further discussion
YuanzhengLei/Unraveling-stochastic-fundamental-diagrams-considering-empirical-knowledge
•
•
The paper analyzes the influence of modeling empirical knowledge in the prior of the stochastic fundamental diagram model and whether empirical knowledge can improve the robustness and accuracy of the proposed model.
Applications
Using early rejection Markov chain Monte Carlo and Gaussian processes to accelerate ABC methods
It uses synthetic data drawn from the simulation model to approximate the posterior distribution.
Computation
A unified generalization of inverse regression via adaptive column selection
A bottleneck of sufficient dimension reduction (SDR) in the modern era is that, among numerous methods, only the sliced inverse regression (SIR) is generally applicable under the high-dimensional settings.
Methodology
Bayesian Model Selection with Latent Group-Based Effects and Variances with the R Package slgf
We have selected data that reveal the shortcomings of classical analyses to emphasize the advantage our method can provide when a latent grouping structure is present.
Methodology
Massively Parallel Computation of Similarity Matrices from Piecewise Constant Invariants
We present a computational framework for piecewise constant functions (PCFs) and use this for several types of computations that are useful in statistics, e. g., averages, similarity matrices, and so on.
Computation Mathematical Software Algebraic Topology 62-04 (Primary) 62R40 (Secondary) G.3; G.4
