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Conformal prediction is a powerful post-hoc framework for uncertainty quantification that provides distribution-free coverage guarantees. However, these guarantees crucially rely on the assumption of exchangeability. This assumption is…

Methodology · Statistics 2025-11-18 M. Stocker , W. Małgorzewicz , M. Fontana , S. Ben Taieb

Studying overlapping coefficients has recently become of great benefit, especially after its use in goodness-of-fit tests. These coefficients are defined as the amount of similarity between two statistical distributions. This research…

Methodology · Statistics 2024-09-06 Omar Eidous , Hala Maqableh

Estimation of reliability and hazard rate is one of the most important problems raised in many applications especially in engineering studies as well as human lifetime. In this regard, different methods of estimation have been used. Each…

Methodology · Statistics 2021-07-27 Hassan Piriaeia , Omid Shojaee

Architectural imperatives due to the slowing of Moore's Law, the broad acceptance of relaxed semantics and the O(n!) worst case verification complexity of generating sequential histories motivate a new approach to concurrent correctness.…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-17 Victor Cook , Christina Peterson , Zachary Painter , Damian Dechev

Measures of relative variability, such as the Pearson's coefficient of variation (CV$_p$), give much insight into the spread of lifetime distributions, like the Weibull distribution. The estimation of the Weibull CV$_p$ in modern statistics…

Methodology · Statistics 2025-11-21 Bankitdor M Nongrum , Adarsha Kumar Jena

Conformal prediction is a non-parametric technique for constructing prediction intervals or sets from arbitrary predictive models under the assumption that the data is exchangeable. It is popular as it comes with theoretical guarantees on…

Machine Learning · Statistics 2025-12-01 Jase Clarkson , Wenkai Xu , Mihai Cucuringu , Yvik Swan , Gesine Reinert

In this paper, we consider the problem of making distributionally robust, skeptical inferences for the multi-label problem, or more generally for Boolean vectors. By distributionally robust, we mean that we consider a set of possible…

Machine Learning · Statistics 2022-05-03 Yonatan Carlos Carranza Alarcón , Sébastien Destercke

Modeling is a challenging topic and using parametric models is an important stage to reach flexible function for modeling. Weibull distribution has two parameters which are shape $\alpha$ and scale $\beta$. In this study, bimodality…

Methodology · Statistics 2020-12-03 Roberto Vila , Mehmet Niyazi Çankaya

We investigate a coherent feedback squeezer that uses quantum coherent feedback (measurement-free) control. Our squeezer is simple, easy to implement, robust to the gain fluctuation, and broadband compared to the existing squeezers because…

We introduce a kernel-based goodness-of-fit test for censored data, where observations may be missing in random time intervals: a common occurrence in clinical trials and industrial life-testing. The test statistic is straightforward to…

Methodology · Statistics 2018-10-11 Tamara Fernández , Arthur Gretton

Structural failure time models are causal models for estimating the effect of time-varying treatments on a survival outcome. G-estimation and artificial censoring have been proposed to estimate the model parameters in the presence of…

Methodology · Statistics 2019-02-19 Shu Yang , Karen Pieper , Frank Cools

The purpose of this report is to look at the measures of importance of components in systems in terms of reliability. In the first work of Birnbaum (1968) on this subject, many interesting studies were created and important indicators were…

Systems and Control · Electrical Eng. & Systems 2021-06-23 Krzysztof J. Szajowski , Małgorzata Średnicka

The problem of distributed dynamic state estimation in wireless sensor networks is studied. Two important properties of local estimates, namely, the consistency and confidence, are emphasized. On one hand, the consistency, which means that…

Information Theory · Computer Science 2016-11-15 Shaocheng Wang , Wei Ren

Statistical analysis on compositional data has gained a lot of attention due to their great potential of applications. A feature of these data is that they are multivariate vectors that lie in the simplex, that is, the components of each…

Handling highly dependent data is crucial in clinical trials, particularly in fields related to ophthalmology. Incorrectly specifying the dependency structure can lead to biased inferences. Traditionally, models rely on three fixed…

Methodology · Statistics 2025-09-30 Shuyi Liang , Takeshi Emura , Chang-Xing Ma , Yijing Xin , Xin-Wei Huang

We give a hybrid two stage design which can be useful to estimate the reliability of a parallel-series and/or by duality a series-parallel system, when the component reliabilities are unknown as well as the total numbers of units allowed to…

Applications · Statistics 2012-12-27 Zohra Benkamra , Mekki Terbeche , Mounir Tlemcani

Estimating the distribution over failures is a key step in validating autonomous systems. Existing approaches focus on finding failures for a small range of initial conditions or make restrictive assumptions about the properties of the…

Robotics · Computer Science 2023-05-18 Harrison Delecki , Anthony Corso , Mykel J. Kochenderfer

Many modern products exhibit high reliability under normal operating conditions. Conducting life tests under these conditions may result in very few observed failures, insufficient for accurate inferences. Instead, accelerated life tests…

Applications · Statistics 2024-09-25 Narayanaswamy Balakrishnan , María Jaenada , Leandro Pardo

We present an extension to the robust phase estimation protocol, which can identify incorrect results that would otherwise lie outside the expected statistical range. Robust phase estimation is increasingly a method of choice for…

This paper concerns the reliability of a pair of coupled oscillators in response to fluctuating inputs. Reliability means that an input elicits essentially identical responses upon repeated presentations regardless of the network's initial…

Chaotic Dynamics · Physics 2007-08-23 Kevin K. Lin , Eric Shea-Brown , Lai-Sang Young
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