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We introduce $\textit{Backward Conformal Prediction}$, a method that guarantees conformal coverage while providing flexible control over the size of prediction sets. Unlike standard conformal prediction, which fixes the coverage level and…

Machine Learning · Statistics 2026-02-13 Etienne Gauthier , Francis Bach , Michael I. Jordan

One central goal of design of observational studies is to embed non-experimental data into an approximate randomized controlled trial using statistical matching. Despite empirical researchers' best intention and effort to create…

Methodology · Statistics 2022-06-22 Kan Chen , Siyu Heng , Qi Long , Bo Zhang

Estimating prevalence, the fraction of a population with a certain medical condition, is fundamental to epidemiology. Traditional methods rely on classification of test samples taken at random from a population. Such approaches to…

Methodology · Statistics 2022-03-25 Paul Patrone , Anthony Kearsley

In the traditional voting manipulation literature, it is assumed that a group of manipulators jointly misrepresent their preferences to get a certain candidate elected, while the remaining voters are truthful. In this paper, we depart from…

Computer Science and Game Theory · Computer Science 2010-01-28 Yvo Desmedt , Edith Elkind

In the context of computational social choice, we study voting methods that assign a set of winners to each profile of voter preferences. A voting method satisfies the property of positive involvement (PI) if for any election in which a…

Computer Science and Game Theory · Computer Science 2021-06-23 Wesley H. Holliday , Eric Pacuit

Win statistics have become increasingly popular for analyzing hierarchical composite endpoints in clinical trials, because they summarize treatment benefit through pairwise comparisons that respect the clinical importance order among…

Methodology · Statistics 2026-04-21 Xi Fang , Guangyu Tong , Yuan Huang , F. Perry Wilson , Patrick J. Heagerty , Fan Li

We show how hidden interesting subelections can be discovered in ordinal elections. An interesting subelection consists of a reasonably large set of voters and a reasonably large set of candidates such that the former have a consistent…

Computer Science and Game Theory · Computer Science 2024-07-29 Łukasz Janeczko , Jérôme Lang , Grzegorz Lisowski , Stanisław Szufa

In a Monte-Carlo test, the observed dataset is fixed, and several resampled or permuted versions of the dataset are generated in order to test a null hypothesis that the original dataset is exchangeable with the resampled/permuted ones.…

Methodology · Statistics 2025-05-05 Lasse Fischer , Aaditya Ramdas

Variational inference has become an increasingly attractive fast alternative to Markov chain Monte Carlo methods for approximate Bayesian inference. However, a major obstacle to the widespread use of variational methods is the lack of…

Machine Learning · Statistics 2020-03-03 Jonathan H. Huggins , Mikołaj Kasprzak , Trevor Campbell , Tamara Broderick

Posterior predictive p-values are a common approach to Bayesian model-checking. This article analyses their frequency behaviour, that is, their distribution when the parameters and the data are drawn from the prior and the model…

Statistics Theory · Mathematics 2015-03-31 Patrick Rubin-Delanchy , Daniel John Lawson

The integrity of elections is central to democratic systems. However, a myriad of malicious actors aspire to influence election outcomes for financial or political benefit. A common means to such ends is by manipulating perceptions of the…

Computer Science and Game Theory · Computer Science 2022-06-22 Junlin Wu , Andrew Estornell , Lecheng Kong , Yevgeniy Vorobeychik

Left censoring can occur with relative frequency when analysing recurrent events in epidemiological studies, especially observational ones. Concretely, the inclusion of individuals that were already at risk before the effective initiation…

Methodology · Statistics 2021-02-24 Gilma Hernández-Herrera , David Moriña , Albert Navarro

In prior work we have introduced an asymptotic threshold of sufficient randomness for causal inference from observational data. In this paper we extend that prior work in three main ways. First, we show how to empirically estimate a lower…

Methodology · Statistics 2023-09-07 Brian Knaeble , Braxton Osting , Placede Tshiaba

The Possible-Winner problem asks, given an election where the voters' preferences over the set of candidates is partially specified, whether a distinguished candidate can become a winner. In this work, we consider the computational…

Computer Science and Game Theory · Computer Science 2018-02-27 Batya Kenig

The single transferable vote (STV) is a system of preferential proportional voting employed in multi-seat elections. Each ballot cast by a voter is a (potentially partial) ranking over a set of candidates. The margin of victory, or simply…

Computer Science and Game Theory · Computer Science 2025-03-26 Michelle Blom , Alexander Ek , Peter J. Stuckey , Vanessa Teague , Damjan Vukcevic

To many statisticians and citizens, the outcome of the most recent U.S. presidential election represents a failure of data-driven methods on the grandest scale. This impression has led to much debate and discussion about how the election…

Other Statistics · Statistics 2017-04-06 Harry Crane , Ryan Martin

Clustering is part of unsupervised analysis methods that consist in grouping samples into homogeneous and separate subgroups of observations also called clusters. To interpret the clusters, statistical hypothesis testing is often used to…

Methodology · Statistics 2022-10-25 Benjamin Hivert , Denis Agniel , Rodolphe Thiébaut , Boris P Hejblum

This paper considers the problem of estimating the variance of a sum of a triangular array of random vectors with heterogeneous means. When random vectors exhibit two-way cluster dependence or weak dependence, standard variance estimators…

Econometrics · Economics 2026-03-13 Luther Yap

In statistical inference, confidence set procedures are typically evaluated based on their validity and width properties. Even when procedures achieve rate-optimal widths, confidence sets can still be excessively wide in practice due to…

Statistics Theory · Mathematics 2025-03-20 Kenta Takatsu

We present a sequential testing method to identify a practically significant effect. We build on the existing mixture sequential probability ratio test (mSPRT) that can sequentially test for a non-zero treatment effect by using a truncated…

Methodology · Statistics 2025-09-10 Kyu Min Shim
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