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We develop tools for selective inference in the setting of group sparsity, including the construction of confidence intervals and p-values for testing selected groups of variables. Our main technical result gives the precise distribution of…

Methodology · Statistics 2016-07-28 Fan Yang , Rina Foygel Barber , Prateek Jain , John Lafferty

This paper proposed a new probability distribution named as inverse xgamma distribution (IXGD). Different mathematical and statistical properties,viz., reliability characteristics, moments, inverse moments, stochastic ordering and order…

Methodology · Statistics 2018-07-04 Abhimanyu Singh Yadav , Sudhansu S. Maiti , Mahendra Saha , Arvind Pandey

Generalized extreme value (GEV) regression is often more adapted when we investigate a relationship between a binary response variable $Y$ which represents a rare event and potentiel predictors $\mathbf{X}$. In particular, we use the…

Methodology · Statistics 2021-05-04 Aba Diop , El Hadji Deme

Ensemble models of graphs are one of the most important theoretical tools to study complex networks. Among them, exponential random graphs (ERGs) have proven to be very useful in the analysis of social networks. In this paper we develop a…

Statistical Mechanics · Physics 2022-11-14 Diego Escribano , José A. Cuesta

Frequent significant deviations of the observed magnitude distribution of anthropogenic seismicity from the Gutenberg-Richter relation require alternative estimation methods for probabilistic seismic hazard assessments. We evaluate five…

Geophysics · Physics 2025-12-22 Francis Tong , Stanisław Lasocki , Beata Orlecka-Sikora

When modelling HIV epidemics, it is important to incorporate set-point viral load and its heritability. As set-point viral load distributions can differ significantly amongst epidemics, it is imperative to account for the observed local…

Populations and Evolution · Quantitative Biology 2018-11-28 Pieter Libin , Laurens Hernalsteen , Kristof Theys , Perpetua Gomes , Ana Abecasis , Ann Nowe

Most theoretical tools available for the analysis of spreading processes over networks assume exponentially distributed transmission and recovery times. In practice, the empirical distribution of transmission times for many real spreading…

Social and Information Networks · Computer Science 2016-11-04 Masaki Ogura , Victor M. Preciado

We study the problem of parameter estimation based on infection data from an epidemic outbreak on a graph. We assume that successive infections occur via contagion; i.e., transmissions can only spread across existing directed edges in the…

Statistics Theory · Mathematics 2018-06-15 Justin Khim , Po-Ling Loh

The probability distribution of the magnitude can be modeled by an exponential distribution according to the Gutenberg-Richter relation. Two alternatives are the truncated exponential distribution (TED) and the cut-off exponential…

Geophysics · Physics 2015-06-19 Mathias Raschke

Observing a load process above high thresholds, modeling it as a pulse process with random occurrence times and magnitudes, and extrapolating life-time maximum or design loads from the data is a common task in structural reliability…

Applications · Statistics 2015-07-28 Baidurya Bhattacharya

Stress is one of the main issues of nowadays lifestyle. If it becomes chronic it can have adverse effects on the human body. Thus, the early detection of stress is crucial to prevent its hurting effects on the human body and have a…

Machine Learning · Computer Science 2024-10-17 Yasin Hasanpoor , Bahram Tarvirdizadeh , Khalil Alipour , Mohammad Ghamari

The graph based approach to multiple testing is an intuitive method that enables a study team to represent clearly, through a directed graph, its priorities for hierarchical testing of multiple hypotheses, and for propagating the available…

Methodology · Statistics 2025-01-07 Cyrus Mehta , Ajoy Mukhopadhyay , Martin Posch

In this paper, we construct a model to describe the transmission of HIV in a homogeneous host population. By considering the specific mechanism of HIV, we derive a model structured in three successive stages: (i) primary infection, (ii)…

Analysis of PDEs · Mathematics 2019-11-18 Mboya Ba , Ramsès Djidjou-Demasse , Mountaga Lam , Jean-Jules Tewa

This work aims at making a comprehensive contribution in the general area of parametric inference for discretely observed diffusion processes. Established approaches for likelihood-based estimation invoke a time-discretisation scheme for…

Methodology · Statistics 2024-01-30 Yuga Iguchi , Alexandros Beskos , Matthew M. Graham

In observational studies, accurately characterizing variance is critical for sample size determination, yet unaccounted-for variability from propensity score estimation and the resulting weights limit the accuracy of standard variance…

Methodology · Statistics 2026-04-24 Taekwon Hong , Daeyoung Lim , Woojung Bae , Yong Ma

We exploit the asymptotic normality of the extreme value theory (EVT) based estimators of the parameters of a symmetric L\'evy-stable distribution, to construct confidence intervals. The accuracy of these intervals is evaluated through a…

Statistics Theory · Mathematics 2019-04-11 Djamel Meraghni , Louiza Soltane

The proliferation of intermittent distributed renewable energy sources (RES) in modern power systems has fundamentally compromised the reliability and accuracy of deterministic net load forecasting. Generative models, particularly diffusion…

Systems and Control · Electrical Eng. & Systems 2025-06-04 Yixiang Huang , Jianhua Pei , Luocheng Chen , Zhenchang Du , Jinfu Chen , Zirui Peng

This paper proposes a novel methodology for probabilistic dynamic security assessment and enhancement of power systems that considers load and generation variability, N-2 contingencies, and uncertain cascade propagation caused by uncertain…

Systems and Control · Electrical Eng. & Systems 2025-05-05 Frédéric Sabot , Pierre-Etienne Labeau , Pierre Henneaux

The problem of finding the expected value of a statistic of a locally stable point process in a bounded region is addressed. We propose an adaptive importance sampling for solving the problem. In our proposal, we restrict the importance…

Machine Learning · Statistics 2025-03-04 Hee-Geon Kang , Sunggon Kim

For a parametric model of distributions, the closest distribution in the model to the true distribution located outside the model is considered. Measuring the closeness between two distributions with the Kullback-Leibler (K-L) divergence,…

Statistics Theory · Mathematics 2025-10-14 Yo Sheena
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