Coping with Information Loss and the Use of Auxiliary Sources of Data: A Report from the NISS Ingram Olkin Forum Series on Unplanned Clinical Trial Disruptions

reidcw/niss-information-loss 22 Jun 2022

Clinical trials disruption has always represented a non negligible part of the ending of interventional studies.

Applications

0
22 Jun 2022

Simulated redistricting plans for the analysis and evaluation of redistricting in the United States: 50stateSimulations

alarm-redist/fifty-states 21 Jun 2022

This article introduces the 50stateSimulations, a collection of simulated congressional districting plans and underlying code developed by the Algorithm-Assisted Redistricting Methodology (ALARM) Project.

Applications Computers and Society

1
21 Jun 2022

Adaptive clinical trial designs with blinded selection of binary composite endpoints and sample size reassessment

martabofillroig/eselect 20 Jun 2022

We consider two-arm randomized controlled trials with a primary composite binary endpoint and an endpoint that consists only of the clinically more important component of the composite endpoint.

Methodology Applications

0
20 Jun 2022

Sparse inference of the human hematopoietic system from heterogeneous and partially observed genomic data

gianluca-sottile/hematopoiesis-network-inference-from-rt-qpcr-data 20 Jun 2022

In this study, we aim to analyse the complex regulatory network that drives the formation of mature red blood cells and platelets from their common precursor.

Methodology

0
20 Jun 2022

Bayesian Lesion Estimation with a Structured Spike-and-Slab Prior

annamenacher/bless 18 Jun 2022

Neural demyelination and brain damage accumulated in white matter appear as hyperintense areas on MRI scans in the form of lesions.

Methodology Applications

0
18 Jun 2022

Iterative importance sampling with Markov chain Monte Carlo sampling in robust Bayesian analysis

Iraices/IIS_MCMC 17 Jun 2022

Bayesian inference under a set of priors, called robust Bayesian analysis, allows for estimation of parameters within a model and quantification of epistemic uncertainty in quantities of interest by bounded (or imprecise) probability.

Computation Methodology 62L20 (Primary), 62P12 (Secondary) G.3

0
17 Jun 2022

Optimal quasi-Bayesian reduced rank regression with incomplete response

tienmt/brrr_missing 17 Jun 2022

We provide a tight oracle inequality, proving that our method is adaptive to the rank of the coefficient matrix.

Methodology Statistics Theory Computation Statistics Theory

0
17 Jun 2022

Ensemble distributional forecasting for insurance loss reserving

agi-lab/reserving-ensemble 17 Jun 2022

This is recognised in practice in the sense that results from different models are often considered, and sometimes combined.

Methodology Risk Management Applications 91G70, 91G60, 62P05, 91B30

0
17 Jun 2022

Bayesian Data Augmentation for Partially Observed Stochastic Compartmental Models

shuyingwang/sir-seir-model-mcmc 17 Jun 2022

Deterministic compartmental models are predominantly used in the modeling of infectious diseases, though stochastic models are considered more realistic, yet are complicated to estimate due to missing data.

Computation Applications Methodology

0
17 Jun 2022

Uncertainty Quantification and the Marginal MDP Model

blakemoya/mdpolya 16 Jun 2022

The paper presents a new perspective on the mixture of Dirichlet process model which allows the recovery of full and correct uncertainty quantification associated with the full model, even after having integrated out the random distribution function.

Computation

0
16 Jun 2022