New papers on Statistics
182 new papers on statistics in the last 7 days, within Math & statistics. These are the 50 Pipette rates most worth reading, with the main result in the authors' own words.
The best of the week
Relegation, promotion and the components of scoring in water polo
Fitted to a new dataset of 940 matches, the model identifies the directly relegated club from the ninth round, before the league table does, predicts the play-out field better than the table, and shows the play-out itself to be close to a coin toss.
PreprintEmpirical Bayes prepivoting under group invariance: false discovery rate control and moderated t-tests
Here we develop the first procedures using moderated t-statistics that (i) control the false discovery rate (FDR) in finite samples under independence across units and null group invariance, without assuming limma's hierarchical model, and (ii) match the power of an oracle local false discovery rate procedure in a sparse asymptotic regime under limma's working model.
PreprintThe Implementation Cost of Fairness in Service Policy Selection
In this research, we identify and study implementation cost as a distinct and equally important dimension of fairness, defined as the sampling effort required to verify fairness and reliably select the best fair policy.
PreprintReal-world useBayesian inference, on-line forecasting and model choice for large VAR models with Cholesky stochastic volatility
We introduce a Markov chain Monte Carlo (MCMC) kernel that mixes better than existing samplers at the same computational complexity.
PreprintClaims a big stepEffects of Repetitive Low-Level Blast Exposure on Mental Health in Veterans
We found that surveyed mortarmen reported statistically significant higher depression (as measured by PHQ-9) than both groups of controls.
PreprintReal-world useA unified framework for estimating direct causal effect under spatial confounding and interference, with the R package spaci
We develop a unified framework that treats both simultaneously.
PreprintReal-world useShort-term rental market occupancy - daily time series for 2017-2022 on 500 markets worldwide
This paper provides a unique, large dataset on global market occupancy for the short-term rental market using data from the American company Wheelhouse.
PreprintThe Spectra of the Henze-Zirkler and Henze-Wagner Operators for BHEP Tests
This paper determines both complete spectra for every dimension and every smoothing parameter .
PreprintClaims a big stepA Projection-Based Approach to Bayesian Age Estimation under Stratigraphic Constraints
The projected posterior is the Wasserstein-closest constrained distribution; it can be computed via isotonic regression on a directed acyclic graph and corrects duration inflation unlike constrained priors.
PreprintPhasing out Monte Carlo: exact acceptance probabilities for mean-spread release rules
One two-dimensional Fourier inversion therefore delivers it for an arbitrary smooth parent - exactly, as an identity, and numerically on a grid whose dimension stays two whatever is - a deterministic alternative to both the simulation and the Normality assumption.
PreprintReal-world usePooling Sequential Evidence Across Hypotheses: Rate-Optimal Multiple Testing at a Fixed Horizon
This rate attains the first-order intersection-delay lower bound as at fixed dimension, configuration, weights, and a long enough horizon.
PreprintReal-world usePhylodynamic inference with the bounded coalescent: a point process perspective
We then develop a Markov chain Monte Carlo procedure for posterior inference of effective population size trajectories that avoids discretization of the likelihood integrals.
PreprintOptimal Biological Dose Combination Finding: A Design Roadmap and Robust Cross-Indication Bayesian Borrowing
We propose a corrected three-by-two taxonomy of OBDC designs by mechanism and objective, a rule-based design (Ji3+3-Comb) closing a documented gap in transparent, model-free combination dose-finding, and a Bayesian Hierarchical Utility-based Cross-indication (BHUC) design that borrows information across indications via a robust mixture prior while discounting non-exchangeable information.
PreprintReal-world useGRACE: A General, Exact Changepoint Calculus
We introduce GRACE, the General Regime-Aware Changepoint Estimator, for an -penalized problem that jointly selects the number and locations of changepoints, segment forms, transition types, and continuous parameters.
PreprintCriminal Justice Risk Assessments with Unreliable Class Assignments
This paper shows how Mondrian conformal prediction sets can increase classification reliability when the classifier is indecisive and provide valid estimates of forecast uncertainty.
PreprintThe ISAC Tradeoff Cliff: Fundamental Limits under Waveform Uncertainty and Finite Blocklength
This shows that the classical finite blocklength reliability results in a fundamentally new insight concerning ISAC systems: when the decoded communication waveforms are reused as sensing references in a data-aided fashion, the communication reliability boundary also acts as a sensing-information bound. {We identify and characterize a sharp transition in sensing performance -- referred to as the Tradeoff Cliff -- arising from finite blocklength reliability effects.} This transition separates the regimes of near-ideal sensing performance from those of excessive estimation error as the communication rate approaches capacity.
Preprint with a published versionReal-world useRolling Conformal Prediction in Sequential Model Training
Remarkably, although the models at times may have entirely different properties and accuracy levels, for exchangeable data it is nonetheless possible to establish a guarantee of marginal coverage, with a familiar universal factor-two guarantee (a worst case guarantee of coverage, as compared to the target level ), without any assumptions of stability or any restrictions on the model training process.
PreprintCounty-Level Heterogeneity in Opioid Harm Reduction and Treatment Effects: A Simulation Modeling Analysis
The same proportional increase in naloxone distribution yields substantially different projected mortality reductions across counties depending on each county's baseline distribution history, a pattern invisible from mortality statistics alone.
PreprintReal-world useChange detection with conformal martingales: new optimal constructions, and suboptimality of existing methods
We propose different conformal e-processes and e-detectors that are provably minimax optimal, with delays and respectively, and have much shorter delays in simulations.
PreprintOptimal sequential decision-making with initiation regimes
These regimes follow human decision-makers up to the point where it becomes more beneficial to initiate a sequential optimal regime, and are guaranteed to outperform both purely human and purely algorithmic decision rules, e.g., based on reinforcement learning algorithms.
PreprintReal-world useAsymptotic Anytime-Valid Quantile Inference under Local Differential Privacy
These results yield asymptotic confidence sequences and, under polynomial chain growth, asymptotic time-uniform coverage.
PreprintFrom Metrics to Decisions in NBA Analytics: A Critical Integrative Review and Decision-Readiness Framework
While its effect on organizational decision quality remains an empirical question, the framework provides a diagnostic and reporting structure for matching decision claims to evidence requirements.
PreprintStatistical Inference for Causal Discovery under Selection and Latent Variables via Single-Target Interventions
We develop a model-free and constraint-query optimal statistical inference framework for causal discovery under latent variables and selection using single-target interventions.
PreprintGeoDose-CP: Graph-Local Conformal Inference for Continuous-Treatment Earth Observation
This study presents GeoDose-CP, a support-aware conformal framework for localized stochastic potential outcomes under continuous or mixed continuous-atomic treatment.
PreprintHybrid Models for Short-Term Sea-Level Forecasting
Results reveal that hybrid models reduce forecast errors by 52.9-54.9% on average relative to HA.
PreprintReal-world useA Geometry-Aware Framework for Clustering Cylindrical Data
We formulate the K-means algorithm for a generic distance on the cylinder and instantiate it with the chordal distance of the ambient space and the geodesic distance along the surface, so that the two versions differ in the metric alone.
PreprintReal-world useSufficiently Reduced Distributional Regression
We propose Sufficiently Reduced Distributional Regression (SRDR), a generative method that combines conditional distribution estimation with nonlinear sufficient dimension reduction (SDR).
PreprintReal-world useExtreme Population Selection under Multistage Sampling design With Applications
Under suitable regularity conditions and without imposing parametric assumptions on the underlying distributions, both algorithms correctly identify the extreme population with a desired level of confidence.
PreprintReal-world useCo-Evolving Zero-Day Jamming: Adaptive Attack Synthesis and Graph Attention-Based Online Detection
This paper addresses these limitations through a two-pronged framework.
PreprintReal-world usePAR2COX: Survival-Informed Tensor Decomposition for Phenotyping and Risk Prediction from Irregular Longitudinal Data
We propose PAR2COX, a joint framework that integrates PARAFAC2 decomposition with Cox proportional hazards model, using patient-specific latent factors as covariates in the likelihood.
PreprintReal-world useOptimal Sequential Annotations for Off-Policy Evaluation
We show how a limited budget for ground-truth data-annotation can be used via doubly-robust OPE with missing rewards, and we optimize variance-optimal annotation probabilities for sequential off-policy evaluation, where the target policy value is estimated from annotated data.
PreprintReal-world useDistributional Balancing with Machine Learning for Clinical Trial Augmentation Using Real-World Data
In this paper, we propose DBML, a method that selects control units from a real world database by matching the distribution between the treatment group and the potential control group, instead of matching units between two groups. DBML has three steps.
PreprintReal-world useInference for sparsely sampled Gauss-Markov processes under outcome-dependent dropout
We develop a likelihood-based estimation framework that, in contrast to existing moment-based methods, avoids the bias induced by outcome-dependent dropout.
PreprintReal-world useShape without scale: an identifiability dichotomy for a bounded tail observed through a non-additive measurement kernel
The shape index alpha is identifiable: for every admissible choice of the class constants, any two observationally equivalent members of a lean class share alpha, determined by a near-endpoint expansion of Q. The rate, namely L and the fixed-scale exceedance p_tau, does not survive.
PreprintIdentifiable Uniqueness of Impulsively Forced, Inert, and Stabilized Body Trajectories
We show when these differences uniquely determine the dynamical class from the observed trajectory and when several classes remain observationally compatible.
PreprintModeling Transition Dynamics and Network Structure in Cross-National Process Data: A Hierarchical Multi-State Survival Framework
We propose a hierarchical framework that integrates a Bayesian multi-state survival model with a network-based representation of transition structure.
PreprintExact maximum likelihood inference for drifted multi-sub-fractional Brownian motion at discrete observation
We show that a complete finite-sample likelihood theory survives nonetheless.
PreprintHeterogeneous survivor average causal effects beyond monotonicity: Applications to a clinical trial evaluating mechanical ventilation strategies
We propose a monotonicity-free framework for identifying conditional survivor average causal effects (CSACE) using an interpretable sensitivity parameter that characterizes latent principal-stratum membership.
PreprintReal-world useIdentification problem and quasi-maximum likelihood estimation for matrix-variate CP-factor models
In contrast, we propose a quasi-maximum likelihood estimation (QMLE) procedure for CP factor models, which allows consistent estimation on the whole identifiable subspace.
PreprintStochastic Epidemic Model Criticism with Neural Evidence Estimation
We propose a model criticism methodology designed for SBI, Neural Evidence Estimation (NEE), that integrates model selection and model misspecification detection.
PreprintWhere quantum and quantum-like methods earn their place in behavioural-trial analysis: three simulation pilots across the RCT pipeline
The three results - one conditional win, one representational win, one honest loss - yield a decision rule for when quantum methods are worth adopting, piloting, or deferring, together with a five-gap research agenda.
PreprintClassical Sufficiency in Quantum Statistical Experiments
We introduce quantum-to-classical sufficiency: relative to a prescribed measurement class, a measurement is sufficient if its induced classical experiment Blackwell-dominates those from every other measurement in the class.
PreprintMulti-Agent Orchestration of 3GPP Channel Estimators
The orchestrator tracks the per-realization oracle to within ~dB and improves the normalized mean-square error (NMSE) over the best fixed strategy by up to ~dB at high SNR, where the low-SNR champion is no longer optimal.
PreprintReal-world useSemiparametric Inference for Dynamic Causal Effects from Observational Time Series
To address these challenges, we develop a semiparametric framework for inference from a single serially dependent time series, integrating debiased machine learning with instrumental variables through buffered block cross-fitting.
PreprintConditional Independence Is Not (Quite) Pointwise Testable
Even restricting to hypotheses with a bounded density on compact subsets of Euclidean spaces, for any sequence of (possibly randomized) tests with pointwise asymptotic level , for every there is a conditionally dependent distribution where the test's limsup power is at most .
PreprintBeyond the Illusion of Power: Calibrating Quasi-Experiments in Observational IS
The serial-correlation component is recoverable by an AR(1)-aware calculator when rho is known, and partially when rho must be estimated from short pre-periods, but panel attrition, staggered-adoption bias, and parallel-trends pretesting are captured by no closed-form formula; exogenous attrition alone costs approx 8 to 11 percentage points at the few-hundred-to-thousand sample sizes IS studies use.
PreprintSpectral divide-and-conquer MCMC for long stationary time series
We propose a frequency-domain framework for scalable Bayesian inference in stationary time series that exploits the asymptotic independence underlying the Whittle likelihood.
PreprintOvercoming Model Misspecification in Bayesian Inference of Molecular Signalling Networks
To confront this reality, we develop a post-Bayesian approach to inference of molecular signalling networks, guided by the principle that uncertainty should not vanish when the statistical model is misspecified, even in the infinite-data limit.
PreprintContext-Adaptive Thresholding for Conditionally Representative Monitoring and Classification
We show how to modify any given threshold-type classifier resp. monitoring rule to achieve representative conditional label prediction by using adapting the threshold to a covariate (the context) to distribute sensitivity while maintaining the false alarm rate.
PreprintFunctional Causal Discovery via Conditional Covariance Ordering
Under functional additive noise models, we propose a new sufficient condition to identify a valid topological ordering based on comparing norms of conditional covariance operators.
Preprint