Tootfinder

Experimental Test of the Principle of Tomographic Locality
Tristan S. Lismer, Kaleb B. Felefele, Robert W. Spekkens, Kevin J. Resch
https://arxiv.org/abs/2506.07775

Experimental Test of the Principle of Tomographic Locality
The principle of tomographic locality states that the operational state of a multipartite system can be fully characterized by the statistics obtained from measurements that are local to the individual subsystems. This property holds in quantum theory and features prominently in axiomatic reconstructions of the theory, where it serves to rule out a wide class of alternatives. For instance, quantum theory with Hilbert spaces defined over the real field (rather than the complex field) is an examp…

TRUST: Test-time Resource Utilization for Superior Trustworthiness
Haripriya Harikumar, Santu Rana
https://arxiv.org/abs/2506.06048 https://

TRUST: Test-time Resource Utilization for Superior Trustworthiness
Standard uncertainty estimation techniques, such as dropout, often struggle to clearly distinguish reliable predictions from unreliable ones. We attribute this limitation to noisy classifier weights, which, while not impairing overall class-level predictions, render finer-level statistics less informative. To address this, we propose a novel test-time optimization method that accounts for the impact of such noise to produce more reliable confidence estimates. This score defines a monotonic subs…

Replaced article(s) found for math.ST. https://arxiv.org/list/math.ST/new
[1/1]:
- Optimal Test-Data Piling in HDLSS Classification with Covariance Heterogeneity
Taehyun Kim, Jeongyoun Ahn, Sungkyu Jung

Selberg's Central Limit Theorem weighted by Linear Statistics of Zeta Zeros
Alessandro Fazzari, Maxim Gerspach, Paolo Minelli
https://arxiv.org/abs/2507.04150

Selberg's Central Limit Theorem weighted by Linear Statistics of Zeta Zeros
We consider the value distribution of the logarithm of the Riemann zeta function on the critical line, weighted by the local statistics of zeta zeros. We show that, with appropriate normalization, it satisfies a complex Central Limit Theorem, provided that the Fourier support of the test function in the linear statistics is sufficiently small. For the imaginary part, we extend this support condition up to its natural barrier under the Riemann Hypothesis. Finally, we prove that the correlation b…

This https://arxiv.org/abs/2504.09567 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Conditional Independence Test Based on Transport Maps
Testing conditional independence between two random vectors given a third is a fundamental and challenging problem in statistics, particularly in multivariate nonparametric settings due to the complexity of conditional structures. We propose a innovative framework for testing conditional independence using transport maps. At the population level, we show that two well-defined transport maps can transform the conditional independence test into an unconditional independence test, this substantial…

Synthetic Turbulence via an Instanton Gas Approximation
Timo Schorlepp, Katharina Kormann, Jeremiah L\"ubke, Tobias Sch\"afer, Rainer Grauer
https://arxiv.org/abs/2507.05945

Synthetic Turbulence via an Instanton Gas Approximation
Sampling synthetic turbulent fields as a computationally tractable surrogate for direct numerical simulations (DNS) is an important practical problem in various applications, and allows to test our physical understanding of the main features of real turbulent flows. Reproducing higher-order Eulerian correlation functions, as well as Lagrangian particle statistics, requires an accurate representation of coherent structures of the flow in the synthetic turbulent fields. To this end, we propose in…

Exoplaneteers Keep Overestimating Sigma Significances
David Kipping, Bj\"orn Benneke
https://arxiv.org/abs/2506.05392 https://ar…

Exoplaneteers Keep Overestimating Sigma Significances
Astronomers, and in particular exoplaneteers, have a curious habit of expressing Bayes factors as frequentist sigma values. This is of course completely unnecessary and arguably rather ill-advised. Regardless, the practice is common - especially in the detection claims of chemical species within exoplanet atmospheres. The current canonical conversion strategy stems from a statistics paper from Sellke et al. (2001), who derived an upper bound on the Bayes factor between the test and null hypothe…

A General Test for Independent and Identically Distributed Hypothesis
Tongyu Li, Jonas Mueller, Fang Yao
https://arxiv.org/abs/2506.22361 https://

A General Test for Independent and Identically Distributed Hypothesis
We propose a simple and intuitive test for arguably the most prevailing hypothesis in statistics that data are independent and identically distributed (IID), based on a newly introduced off-diagonal sequential U-process. This IID test is fully nonparametric and applicable to random objects in general spaces, while requiring no specific alternatives such as structural breaks or serial dependence, which allows for detecting general types of violations of the IID assumption. An easy-to-implement j…

This https://arxiv.org/abs/2405.03024 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

CMB low multipole alignments across WMAP and \emph{Planck} data releases
The first observations of the cosmic microwave background (CMB) from NASA's \emph{Wilkinson Microwave Anisotropy Probe} (WMAP) led to finding `alignment' anomalies not expected from fluctuations in the isotropic cosmological model. We study the data of all 8 full-sky public releases since then to test for anomalous alignments and shapes of the first 60 multipoles, i.e., over the range $2\leq l \leq 61$. We use rotationally invariant and covariant statistics to test isotropy of all subsequent WM…

Semi-tail Units: A Universal Scale for Test Statistics and Efficiency
Paul W. Vos
https://arxiv.org/abs/2506.22910 https://arxiv.org/…

Semi-tail Units: A Universal Scale for Test Statistics and Efficiency
We introduce $ζ$- and $s$-values as quantile-based standardizations that are particularly suited for hypothesis testing. Unlike p-values, which express tail probabilities, $s$-values measure the number of semi-tail units into a distribution's tail, where each unit represents a halving of the tail area. This logarithmic scale provides intuitive interpretation: $s=3.3$ corresponds to the 10th percentile, $s=4.3$ to the 5th percentile, and $s=5.3$ to the 2.5th percentile. For two-tailed tests, $Î…

PatchDSU: Uncertainty Modeling for Out of Distribution Generalization in Keyword Spotting
Bronya Roni Chernyak, Yael Segal, Yosi Shrem, Joseph Keshet
https://arxiv.org/abs/2508.03190

PatchDSU: Uncertainty Modeling for Out of Distribution Generalization in Keyword Spotting
Deep learning models excel at many tasks but rely on the assumption that training and test data follow the same distribution. This assumption often does not hold in real-world speech systems, where distribution shifts are common due to varying environments, recording conditions, and speaker diversity. The method of Domain Shifts with Uncertainty (DSU) augments the input of each neural network layer based on the input feature statistics. It addresses the problem of out-of-domain generalization…

At the edge of Donsker's Theorem: Asymptotics of multiscale scan statistics
Johann K\"ohne, Fabian Mies
https://arxiv.org/abs/2506.05112 https://

At the edge of Donsker's Theorem: Asymptotics of multiscale scan statistics
For nonparametric inference about a function, multiscale testing procedures resolve the need for bandwidth selection and achieve asymptotically optimal detection performance against a broad range of alternatives. However, critical values strongly depend on the noise distribution, and we argue that existing methods are either statistically infeasible, or asymptotically sub-optimal. To address this methodological challenge, we show how to develop a feasible multiscale test via weak convergence ar…

Dependency on Meta AI Chatbot in Messenger Among STEM and Non-STEM Students in Higher Education
Hilene E. Hernandez, Rhiziel P. Manalese, Roque Francis B. Dianelo, Jaymark A. Yambao, Almer B. Gamboa, Lloyd D. Feliciano, Mike Haizon M. David, Freneil R. Pampo, John Paul P. Miranda
https://arxiv.org/abs/2507.21059

Dependency on Meta AI Chatbot in Messenger Among STEM and Non-STEM Students in Higher Education
To understand the potential dependency of tertiary students regarding Meta AI in the academic context. This descriptive cross-sectional study surveyed 872 tertiary students from public and private institutions in Luzon, Philippines. Demographic information and perceptions on Meta AI dependency based on existing literature were collected. Descriptive statistics were used to summarize the data and differences between STEM and non-STEM students were analyzed using the Mann-Whitney U test. The resu…

An Improved Inference for IV Regressions
Liyu Dou, Pengjin Min, Wenjie Wang, Yichong Zhang
https://arxiv.org/abs/2506.23816 https://a…

An Improved Inference for IV Regressions
Researchers often report empirical results that are based on low-dimensional IVs, such as the shift-share IV, together with many IVs. Could we combine these results in an efficient way and take advantage of the information from both sides? In this paper, we propose a combination inference procedure to solve the problem. Specifically, we consider a linear combination of three test statistics: a standard cluster-robust Wald statistic based on the low-dimensional IVs, a leave-one-cluster-out Lagra…

Replaced article(s) found for stat.OT. https://arxiv.org/list/stat.OT/new
[1/1]:
- Jackknife Empirical Likelihood Ratio Test for Cauchy Distribution
Ganesh Vishnu Avhad, Ananya Lahiri, Sudheesh K. Kattumannil

This https://arxiv.org/abs/2411.10121 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Quadratic Form based Multiple Contrast Tests for Comparison of Group Means
Comparing the mean vectors across different groups is a cornerstone in the realm of multivariate statistics, with quadratic forms commonly serving as test statistics. However, when the overall hypothesis is rejected, identifying specific vector components or determining the groups among which differences exist requires additional investigations. Conversely, employing multiple contrast tests (MCT) allows conclusions about which components or groups contribute to these differences. However, they …

Two-Sample Covariance Inference in High-Dimensional Elliptical Models
Nina D\"ornemann
https://arxiv.org/abs/2507.02640 https://…

Two-Sample Covariance Inference in High-Dimensional Elliptical Models
We propose a two-sample test for large-dimensional covariance matrices in generalized elliptical models. The test statistic is based on a U-statistic estimator of the squared Frobenius norm of the difference between the two population covariance matrices. This statistic was originally introduced by Li and Chen (2012, AoS) for the independent component model. As a key theoretical contribution, we establish a new central limit theorem for the U-statistics under elliptical data, valid under both t…

Independence Testing for Mixed Data
Dana Bucalo Jeli\'c, Marija Cupari\'c, Bojana Milo\v{s}evi\'c
https://arxiv.org/abs/2507.20609 https://arxi…

Independence Testing for Mixed Data
We consider the problem of testing independence in mixed-type data that combine count variables with positive, absolutely continuous variables. We first introduce two distinct classes of test statistics in the bivariate setting, designed to test independence between the components of a bivariate mixed-type vector. These statistics are then extended to the multivariate context to accommodate: (i) testing independence between vectors of different types and possibly different dimensions, and (ii) …

Euclid preparation: Expected constraints on initial conditions
Collaboration, Finelli, Akrami, Andrews, Ballardini, Casas, Karagiannis, Sakr, Valiviita, Alestas, Bartolo, Bermejo-Climent, Nesseris, Paoletti, Sapone, Tutusaus, Ach\'ucarro, Ca\~nas-Herrera, Jasche, Lavaux, Aghanim, Altieri, Amara, Amendola, Andreon, Auricchio, Baccigalupi, Bagot, Baldi, Bardelli, Battaglia, Biviano, Branchini, Brescia, Camera, Capobianco, Carbone, Carretero, Castellano, Castignani, Cavuoti, Chambers,…

Euclid preparation: Expected constraints on initial conditions
The Euclid mission of the European Space Agency will deliver galaxy and cosmic shear surveys, which will be used to constrain initial conditions and statistics of primordial fluctuations. We present highlights for the Euclid scientific capability to test initial conditions beyond LCDM with the main probes, i.e. 3D galaxy clustering from the spectroscopic survey, the tomographic approach to 3x2pt statistics from photometric galaxy survey, and their combination. We provide Fisher forecasts from t…

Distribution-free data-driven smooth tests without $\chi^2$
Xiangyu Zhang, Sara Algeri
https://arxiv.org/abs/2508.01973 https://arxiv.org/pdf/2508.01973

Distribution-free data-driven smooth tests without $χ^2$
This article demonstrates how recent developments in the theory of empirical processes allow us to construct a new family of asymptotically distribution-free smooth test statistics. Their distribution-free property is preserved even when the parameters are estimated, model selection is performed, and the sample size is only moderately large. A computationally efficient alternative to the classical parametric bootstrap is also discussed.

A Relativity-Based Framework for Statistical Testing Guided by the Independence of Ancillary Statistics: Methodology and Nonparametric Illustrations
Albert Vexler, Douglas Landsittel
https://arxiv.org/abs/2507.11816

A Relativity-Based Framework for Statistical Testing Guided by the Independence of Ancillary Statistics: Methodology and Nonparametric Illustrations
This paper introduces a decision-theoretic framework for constructing and evaluating test statistics based on their relationship with ancillary statistics-quantities whose distributions remain fixed under the null and alternative hypotheses. Rather than focusing solely on maximizing discriminatory power, the proposed approach emphasizes reducing dependence between a test statistic and relevant ancillary structures. We show that minimizing such dependence can yield most powerful (MP) procedures.…

Optimal-Transport Based Multivariate Goodness-of-Fit Tests
Zden\v{e}k Hl\'avka, \v{S}\'arka Hudecov\'a, Simos G. Meintanis
https://arxiv.org/abs/2507.23490 https://

Optimal-Transport Based Multivariate Goodness-of-Fit Tests
Characteristic-function based goodness-of-fit tests are suggested for multivariate observations. The test statistics, which are straightforward to compute, are defined as two-sample criteria measuring discrepancy between multivariate ranks of the original observations and the corresponding ranks obtained from an artificial sample generated from the reference distribution under test. Multivariate ranks are constructed using the theory of the optimal measure transport, thus rendering the tests of…

An exact test for the mixed membership stochastic block model
Sourav Majumdar
https://arxiv.org/abs/2507.14464 https://arxiv.org/pdf/…

An exact test for the mixed membership stochastic block model
We present the first finite-sample goodness-of-fit test for the mixed membership stochastic block model (MMSBM). Using algebraic statistics theory, we derive a Markov basis that lets a Metropolis-Hastings sampler explore exactly the set of networks compatible with a fitted MMSBM. The resulting exact $p$-value, based on a partial conjunction statistic, requires no asymptotic approximations. Simulations show nominal size and strong power against misspecified block numbers and connection patterns.

A Bayesian Approach to Estimating Effect Sizes in Educational Research
Yannis B\"ahni
https://arxiv.org/abs/2507.14848 https://a…

A Bayesian Approach to Estimating Effect Sizes in Educational Research
In educational research, a first step in the descriptive analysis of data from any psychometric measurement of the performance of subjects in tests at different time points and between groups is to compute relative measures of learning gains and learning achievements. For these effect sizes, there are classical approaches coming from frequentistic statistics like Student's or Welch's $t$-test with their own strengths and weaknesses. In this paper, we propose a purely Bayesian approach for analy…

Likelihood Ratio test for Poisson graph
Chen Shuyan, Liu Xin, Wang Shaoli
https://arxiv.org/abs/2506.18778 https://arxiv.org/pdf/2506…

Likelihood Ratio test for Poisson graph
Directed acyclic graphs are widely used to describe the causal effects among random variables, and the inference of those causal effects has become an popular topic in statistics and machine learning, and has wide applications in neuroinformatics, bioinformatics and so on. However, most studies focus on the estimation or inference of the directional relations among continuous random variables, those among discrete random variables have not gained much attentions. In this article we focus on the…

Independent increments and group sequential tests
Anastasios A. Tsiatis, Marie Davidian
https://arxiv.org/abs/2506.15599 https://arxi…

Independent increments and group sequential tests
Widely used methods and software for group sequential tests of a null hypothesis of no treatment difference that allow for early stopping of a clinical trial depend primarily on the fact that sequentially-computed test statistics have the independent increments property. However, there are many practical situations where the sequentially-computed test statistics do not possess this property. Key examples are in trials where the primary outcome is a time to an event but where the a…

Replaced article(s) found for math.ST. https://arxiv.org/list/math.ST/new
[1/1]:
- Bootstrap-based tests for the total time on test and the excess wealth orders
Tommaso Lando, Sirio Legramanti

A powerful procedure that controls the false discovery rate with directional information
Zhaoyang Tian, Kun Liang, Pengfei Li
https://arxiv.org/abs/2507.15631

A powerful procedure that controls the false discovery rate with directional information
In many multiple testing applications in genetics, the signs of test statistics provide useful directional information, such as whether genes are potentially up- or down-regulated between two experimental conditions. However, most existing procedures that control the false discovery rate (FDR) are $p$-value based and ignore such directional information. We introduce a novel procedure, the signed-knockoff procedure, to utilize the directional information and control the FDR in finite samples. We…