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When assessing the causal effect of a binary exposure using observational data, confounder imbalance across exposure arms must be addressed. Matching methods, including propensity score-based matching, can be used to deconfound the causal…

Methodology · Statistics 2024-10-01 Ernesto Ulloa-Pérez , Marco Carone , Alex Luedtke

Probability distributions and densities are derived for the excess and deficiency of the intensity or instantaneous energy (quasi-static power) associated with a $p$-dimensional random vector field. Explicit expressions for the exact…

Data Analysis, Statistics and Probability · Physics 2021-08-27 Luk R. Arnaut

There has been growing attention on how to effectively and objectively use covariate information when the primary goal is to estimate the average treatment effect (ATE) in randomized clinical trials (RCTs). In this paper, we propose an…

Methodology · Statistics 2020-09-01 Yuanyao Tan , Xialing Wen , Wei Liang , Ying Yan

Polygenic risk scores (PRS) developed from genome-wide association studies (GWAS) can be used for risk stratification by quantifying the genetic contribution to disease, and many clinical applications have been proposed. Bayesian methods…

Methodology · Statistics 2026-03-11 Yuzheng Dun , Nilanjan Chatterjee , Jin Jin , Akihiko Nishimura

Epidemic models currently play a central role in our attempts to understand and control infectious diseases. Here, we derive a model for the diffusion limit of stochastic susceptible-infectious-removed (SIR) epidemic dynamics on a…

Populations and Evolution · Quantitative Biology 2013-09-30 Matthew Graham , Thomas House

Conditional Autoregressive Value-at-Risk and Conditional Autoregressive Expectile have become two popular approaches for direct measurement of market risk. Since their introduction several improvements both in the Bayesian and in the…

Statistical Finance · Quantitative Finance 2019-10-01 Marco Bottone , Mauro Bernardi , Lea Petrella

We propose a new method to combine adaptive processes with a class of entropy estimators for the case of streams of data. Starting from a first estimation obtained from a batch of initial data, model parameters are estimated at each step by…

Signal Processing · Electrical Eng. & Systems 2020-01-15 Mario Angelelli , Enrico Ciavolino , Paola Pasca

Reinforcement learning can learn amortised design policies for designing sequences of experiments. However, current amortised methods rely on estimators of expected information gain (EIG) that require an exponential number of samples on the…

Machine Learning · Computer Science 2024-02-06 Tom Blau , Iadine Chades , Amir Dezfouli , Daniel Steinberg , Edwin V. Bonilla

The piecewise exponential model is a flexible non-parametric approach for time-to-event data, but extrapolation beyond final observation times typically relies on random walk priors and deterministic knot locations, resulting in unrealistic…

Methodology · Statistics 2025-05-12 Luke Hardcastle , Samuel Livingstone , Gianluca Baio

The objective is to model longitudinal and survival data jointly taking into account the dependence between the two responses in a real HIV/AIDS dataset using a shared parameter approach inside a Bayesian framework. We propose a linear…

Applications · Statistics 2016-05-02 Rui Martins

We consider a single outbreak susceptible-infected-recovered (SIR) model and corresponding estimation procedures for the effective reproductive number $\mathcal{R}(t)$. We discuss the estimation of the underlying SIR parameters with a…

Populations and Evolution · Quantitative Biology 2020-04-16 Ariel Cintrón-Arias , Carlos Castillo-Chávez , Luís M. A. Bettencourt , Alun L. Lloyd , H. T. Banks

Probabilistic regression models typically use the Maximum Likelihood Estimation or Cross-Validation to fit parameters. These methods can give an advantage to the solutions that fit observations on average, but they do not pay attention to…

Applications · Statistics 2022-05-24 Naoufal Acharki , Antoine Bertoncello , Josselin Garnier

This paper studies epidemic processes over discrete-time periodic time-varying networks. We focus on the susceptible-infected-susceptible (SIS) model that accounts for a (possibly) mutating virus. We say that an agent is in the disease-free…

Systems and Control · Electrical Eng. & Systems 2020-11-18 Sebin Gracy , Philip. E. Pare , Henrik Sandberg , Karl Henrik Johansson

A theory of flow stress, including the yield strength is proposed for the class of PC materials with equilibrium defect structure (EDS), which is established in the PC material after series of $N_0$ similar treatments of severe plastic…

Materials Science · Physics 2021-03-09 Alexander A. Reshetnyak

Motivated by the need to study the molecular mechanism underlying Type 1 Diabetes (T1D) with the gene expression data collected from both the patients and healthy controls at multiple time points, we propose an innovative method for jointly…

Methodology · Statistics 2018-12-10 Bochao Jia , Faming Liang , the TEDDY Study Group

An informative sampling design leads to the selection of units whose inclusion probabilities are correlated with the response variable of interest. Model inference performed on the resulting observed sample will be biased for the population…

Methodology · Statistics 2018-06-29 Matthew R. Williams , Terrance D. Savitsky

Extreme events with potential deadly outcomes, such as those organized by terror groups, are highly unpredictable in nature and an imminent threat to society. In particular, quantifying the likelihood of a terror attack occurring in an…

Applications · Statistics 2021-11-02 Lekha Patel , Lyndsay Shand , J. Derek Tucker , Gabriel Huerta

Using the maximum-entropy method, we calculate the end-to-end distance distribution of the force stretched chain from the moments of the distribution, which can be obtained from the extension-force curves recorded in single-molecule…

Soft Condensed Matter · Physics 2009-11-07 Luru Dai , Fei Liu , Zhong-can Ou-Yang

Throughout the course of an epidemic, the rate at which disease spreads varies with behavioral changes, the emergence of new disease variants, and the introduction of mitigation policies. Estimating such changes in transmission rates can…

Methodology · Statistics 2022-11-29 Jenny Huang , Raphaël Morsomme , David Dunson , Jason Xu

We introduce a new version of forward stepwise regression. Our modification finds solutions to regression problems where the selected predictors appear in a structured pattern, with respect to a predefined distance measure over the…

Methodology · Statistics 2011-08-02 Daniel Percival , Kathryn Roeder , Roni Rosenfeld , Larry Wasserman
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