Probability & Statistics · Mathematics & Statistics
Methodology
The newest papers in Methodology that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
353 papers, from 4 September 2026 to 5 November 2026: 353 arXiv preprints.
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Newest papers, page 17
Assumption-Lean Inference for Spectral Differential Network Analysis of High-Dimensional Time Series
Network analysis for multivariate time series is popular in many fields, from neuroscience to seismology.Hierarchical Clustering Can Jointly Satisfy Richness, Consistency, and Scale Invariance
Despite its ubiquity, clustering lacks a universally accepted definition of what is a cluster.Market-Informed Networks for Modeling and Forecast Evaluation of Financial Extremes
Modeling the joint distribution of extreme values in high-dimensional financial time series is challenging because extremes are sparse and locally extreme observations are not necessarily extreme…Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact
Generative artificial intelligence changes how firms reach customers, but standard marketing data do not record how often users see and notice a firm's name in generated answers.The Anatomy and Boundary of Adaptation under Temporal Tabular Shift
Prequential adaptation of frozen tabular foundation models under temporal drift, with each label revealed only after prediction, helps some deployments and harms others, yet current practice does…Optimal Value Inference for Reinforcement Learning
We study offline inference for the optimal value in reinforcement learning.Dynamical Non-compensatory Multidimensional IRT Model Using Variational Approximation
Multidimensional item response theory (MIRT) is a statistical test theory that precisely estimates multiple latent skills of learners from the responses in a test.Semiparametric Inference for Conditional Shapley Feature Importance
Shapley values are widely used for post-hoc feature attribution, but most estimators return point quantities and do not quantify uncertainty, and popular implementations sample out-of-coalition…Likelihood-free inference with nuisance parameters through normalizing flows
We present a simple decomposition of a neural-network-based normalizing flow that naturally uncovers a pivotal statistic (or something close) in the presence of nuisance parameters, based only on a…Processing and classifying bird songs using wavelet techniques and supervised learning
This study proposes an integrated framework for the processing and classification of invasive bird species vocalizations within natural soundscapes, characterized by high levels of environmental…The Elliptically Optimal Confidence Interval: A Bivariate Extension of Wilson's Score Method
Constructing a confidence interval for the difference between two independent binomial proportions involves a nuisance direction that is not identified by the estimand.Distribution-free inference on the number of changepoints
Suppose we are given an ordered sequence of independent data whose distribution changes $K$ times at unknown locations, for some unknown $K \geq 0$.Geographically Regularized AUC-Maximizing Personalized Federated Learning
Accurate diagnostic and risk-prediction models are important for supporting clinical decision-making during infectious disease outbreaks.Instability in Patient Clustering: A Multiverse Analysis of Unsupervised Clustering in the CENTER-TBI cohort
Understanding patient heterogeneity is key to improving prognostic modeling in traumatic brain injury (TBI).Dynamic Latent Space Modeling of Inhomogeneous Poisson Network Processes with Applications to International Relations
We study continuous-time relational event data, where time-stamped dyadic interactions reflect both individual node propensities and evolving relational proximity.A Closed-Form Estimator and Diagnostic Battery for Anchor-Judge Error Correlation, Under a Single-Common-Factor Model
When an external reference set (an anchor) is used to decompose an LLM-judge panel's error into a quality signal and a shared common-mode error, standard practice assumes the anchor is…Accountable and uncertainty-aware evaluation of sensor-based AI under distribution shift: devices, subjects, and nearly three years underground
Sensor-based AI systems are rarely operated under the conditions under which they were trained: devices, personnel and recording epochs change, and each change degrades performance in ways a random…Real-time and adaptive anomaly detection algorithm for cyclostationary models
This article introduces PeriodicCALM, an effective real-time anomaly detection framework designed for cyclostationary data streams.MiNCE: Nonparametric, Strongly Consistent Confidence Envelopes for Band-Limited Functions and their Smoothed Spectra
Minimum-norm confidence envelope strategies offer a nonparametric approach to constructing nonasymptotic, simultaneous confidence regions for band-limited functions, exploiting the theory of…Differentially Private Average Treatment Effect Estimation by Propensity Score Blocking
Average treatment effect (ATE) estimation in observational studies is a fundamental statistical tool used frequently in social science, medicine, and other fields.