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The study of times to nonterminal events of different types and their interrelation is a compelling area of interest. The primary challenge in analyzing such multivariate event times is the presence of informative censoring by the terminal…

Methodology · Statistics 2025-07-29 Xinyuan Chen , Yiwei Li , Qian M. Zhou

Sample size determination is crucial in experimental design, especially in traffic and transport research. Frequentist statistics require a fixed sample size determined by power analysis, which cannot be adjusted once the experiment starts.…

Methodology · Statistics 2025-03-04 Xiaomi Yang , Carol Flannagan , Jonas Bärgman

We propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We develop our copula for first order Markov series, and extend it to higher orders and multivariate series. We derive the copula of a…

Applications · Statistics 2017-01-26 Rubén Loaiza-Maya , Michael S. Smith , Worapree Maneesoonthorn

In prevalent cohort studies where subjects are recruited at a cross-section, the time to an event may be subject to length-biased sampling, with the observed data being either the forward recurrence time, or the backward recurrence time, or…

Statistics Theory · Mathematics 2019-04-05 Pourab Roy , Jason P. Fine , Michael R. Kosorok

We establish new conditions for obtaining uniform bounds on the moments of discrete-time stochastic processes. Our results require a weak negative drift criterion along with a state-dependent restriction on the sizes of the one-step jumps…

Probability · Mathematics 2022-06-02 Arnab Ganguly , Debasish Chatterjee

Cox's proportional hazards model is one of the most popular statistical models to evaluate associations of exposure with a censored failure time outcome. When confounding factors are not fully observed, the exposure hazard ratio estimated…

Methodology · Statistics 2022-01-04 Linbo Wang , Eric Tchetgen Tchetgen , Torben Martinussen , Stijn Vansteelandt

Rare events in molecular dynamics are often related to noise-induced transitions between different macroscopic states (e.g., in protein folding). A common feature of these rare transitions is that they happen on timescales that are on…

Probability · Mathematics 2026-01-06 Carsten Hartmann , Annika Jöster , Christof Schütte , Alexander Sikorski , Marcus Weber

This work extends causal inference with stochastic confounders. We propose a new approach to variational estimation for causal inference based on a representer theorem with a random input space. We estimate causal effects involving latent…

Machine Learning · Statistics 2021-01-26 Thanh Vinh Vo , Pengfei Wei , Wicher Bergsma , Tze-Yun Leong

In this paper, we solve the existence problem of optimal stopping problem under some kind of nonlinear expectation named g_\Gamma expectation which was recently introduced in Peng, S.G. and Xu, M.Y. [8]. Our method based on our preceding…

Probability · Mathematics 2011-05-12 Helin Wu

Sellke and Siegmund (1983) developed the Brownian approximation to the Cox partial likelihood score as a process of calendar time, laying the foundation for group sequential analysis of survival studies. We extend their results to cover…

Statistics Theory · Mathematics 2013-12-24 Xiaolong Luo , Gongjun Xu , Zhiliang Ying

In a group sequential clinical trial, accumulated data are analysed at numerous time-points in order to allow early decisions about a hypothesis of interest. These designs have historically been recommended for their ethical, administrative…

Computation · Statistics 2017-11-29 Michael Grayling , James Wason , Adrian Mander

We present a general approach for studying autoregressive categorical time series models with dependence of infinite order and defined conditional on an exogenous covariate process. To this end, we adapt a coupling approach, developed in…

Statistics Theory · Mathematics 2019-08-01 Lionel Truquet

Given a heterogeneous time-series sample, the objective is to find points in time (called change points) where the probability distribution generating the data has changed. The data are assumed to have been generated by arbitrary unknown…

Machine Learning · Statistics 2015-05-13 Azadeh Khaleghi , Daniil Ryabko

Prevalent cohort sampling is commonly used to study the natural history of a disease when the disease is rare or it usually takes a long time to observe the failure event. It is known, however, that the collected sample in this situation is…

Methodology · Statistics 2022-09-05 Omidali Aghababaei Jazi

Causal phenomena associated with rare events occur across a wide range of engineering problems, such as risk-sensitive safety analysis, accident analysis and prevention, and extreme value theory. However, current methods for causal…

Machine Learning · Statistics 2023-07-19 Chih-Yuan Chiu , Kshitij Kulkarni , Shankar Sastry

In the first part of the paper, we consider a discrete-time stochastic control system. We show that, under certain conditions, the set of random occupational measures generated by the state-control trajectories of the system as well as the…

Optimization and Control · Mathematics 2022-12-21 Lucas Gamertsfelder

We propose a method based on continuous time Markov chain approximation to compute the distribution of Parisian stopping times and price Parisian options under general one-dimensional Markov processes. We prove the convergence of the method…

Computational Finance · Quantitative Finance 2021-07-15 Gongqiu Zhang , Lingfei Li

In this paper we compute the stopping times in the game Rock-Paper-Scissors. By exploiting the recurrence relation we compute the mean values of stopping times. On the other hand, by constructing a transition matrix for a Markov chain…

Probability · Mathematics 2019-06-03 Kyeonghoon Jeong , Hyun Jae Yoo

In a real-life setting, little is known regarding the effectiveness of statins for primary prevention among older adults, and analysis of observational data can add crucial information on the benefits of actual patterns of use. Latent class…

Methodology · Statistics 2023-10-18 Awa Diop , Caroline Sirois , Jason Robert Guertin , Denis Talbot

Pair-copula constructions are flexible dependence models that use bivariate copulas as building blocks. In this paper, we use generalized additive models to extend them by allowing covariates effects. Borrowing ideas from a traditionally…

Methodology · Statistics 2017-08-17 Thibault Vatter , Thomas Nagler