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883 papers in math.ST · page 6
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Energy distance scan detects single change points with permutation calibration
Single Change-Point Detection via Energy Distance with Application to Genomic Data
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Mutual information stays fixed in time-reversed Young interferometry
Entropic Reciprocity in Time-Reversed Young Interferometry
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Penalized likelihood ensures existence in sparse network models
Penalized Likelihood for Dyadic Network Formation Models with Degree Heterogeneity
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The paper models networked systems that switch regimes and carry memory of past states
Quenched Amplification and Tail Shaping in Networked Systems with Memory and Regime Switching
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Long memory switched systems exhibit bursts despite average stability
Intermittency induced by long memory under stochastic regime switching
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Bootstrap adapts to four clustering regimes for valid tests
Bootstrap Inference under General Two-way Clustering with Serially and Spatially Dependent Common Effects
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Supersymmetric reduction recasts Royen's Gaussian inequality proof
Royen's proof of the Gaussian correlation inequality as a supersymmetric dimensional reduction
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Coupled neural nets price American options under Heston
American Options Pricing under Heston Model via Curriculum Learning in Coupled PINNs
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Predictive Bayesian credible sets can have near-zero coverage
Concentration and Calibration in Predictive Bayesian Inference
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Profile estimator attains minimax bound for hyperbolic location inference
Profile Likelihood Inference for Anisotropic Hyperbolic Wrapped Normal Models on Hyperbolic Space
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Bivariate mixtures let MLE beat square-root convergence
A Simple Bivariate Example of Fast Convergence Rates for Maximum Likelihood Estimates
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Bivariate observation simplifies stock return MLE to regression
Modeling Stock Returns and Volatility Using Bivariate Gamma Generalized Laplace Law
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Kernel tests for independence work with weakly dependent data
Kernel-based independence and mean independence tests for weakly dependent data
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Decoupled descent forces train error to match test error
Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing
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Wild bootstrap max-test detects high-dimensional predictors
A High Dimensional Wild Bootstrap Max-Test for Detecting the Presence of Significant Predictors
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New quarticity estimator achieves stable CLT at rate 1/sqrt(Δ_n)
A note on estimation of quarticity based on spot volatility
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Bayesian one-pass algorithm attains optimal posterior convergence
The Bernstein-von Mises theorem for Bayesian one-pass online learning
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Estimators stay consistent on subsampled slow-fast data
Statistical Inference for Homogenization Limits Driven by Wiener or Hermite Processes
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Tilted density scores equal original scores at shifted location and time
Technical Note on Relating Scores of Tilted Distributions
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HyCNNs approximate quadratics with exponentially fewer parameters
Hyper Input Convex Neural Networks for Shape Constrained Learning and Optimal Transport
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The paper proves that any random variable whose moment generating function is bounded…
Sharp One-Dimensional Sub-Gaussian Comparison in Convex Order
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Black-box selection leaks at most the total variation distance to conditional law
A Leakage Bound for Confidence Sets after Black-Box Selection
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Bayesian model produces prediction curves for cause-specific risks over time
Principled Estimation and Prediction with Competing Risks: a Bayesian Nonparametric Approach
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Consistent rank correlation matrices converge to semicircle law
Limiting spectral distributions of large consistent rank correlation matrices
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This paper derives limiting eigenvalue locations and eigenvector projections for scaled…
Asymptotics of ultra-high-dimensional generalized spiked sample covariance matrix
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Adaptive CIs in two-groups model scale as σ(n^{-1/4} + ε term)
Adaptive Confidence Intervals in Efron's Gaussian Two-Groups Model
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Observability of latent states identifies causal treatment effects in continuous time
Observable Neural ODEs for Identifiable Causal Forecasting in Continuous Time
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Observability required to identify causal effects in continuous time
Observable Neural ODEs for Identifiable Causal Forecasting in Continuous Time
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Geometric records yield consistent MLE for Pareto tail index
Estimating the tail index of Pareto-type distributions from geometric records
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Semiparametric model adds flexible spatial term to linear covariates
A semiparametric autorregresive spatial prediction model
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Rates for Markov kernels bound variances of Lipschitz functions
Implications of weak convergence rates of Markov transition kernels
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Small clean data purifies noisy labels for classification
Model-agnostic information transfer and fusion for classification with label noise
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Test detects constant volatility at minimax-optimal rate
Sharp adaptive nonparametric testing for constant volatility
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New method balances seen and unseen covariates while adapting trial allocations
CBARA: Covariate-Balanced-and-Adjusted Response-Adaptive Randomization
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New randomization balances observed and unobserved covariates
CBARA: Covariate-Balanced-and-Adjusted Response-Adaptive Randomization
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Distributed RLS converges almost surely for infinite-parameter models
Distributed adaptive estimation for stochastic large regression models
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Diffusion threshold MLE converges at n^{-(1+γ)/2} rate
Self-organized regime switching in null-recurrent dynamics
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Exact closed forms replace recursions for scan statistics
Exact Closed-Form Formulae for Linear and Circular Continuous Scan Statistics: $P_c(N - 1; N, w)$, $P_c(3; N, w)$, and $P(3; N, w)$
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Optimal Kelly wealth growth equals bipolar KL limit
The optimal betting wealth growth rate
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PCA estimator lowers error for population mean under multicollinearity
Principal Component Based Estimation of Finite Population Mean under Multicollinearity
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Context kernel separates neighborhood from fit in local regression
Generalized Local Polynomial Regression with Decomposed Context-Aware Kernels
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Tail allocation recovers shortest single-interval conformal predictors
Tail allocation for conformal prediction intervals
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Elite SVMs steer slacks toward trusted reference benchmarks
Elite-Driven Support Vector Machines for Classification
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Sample splitting yields valid tests for linear systems with unknown coefficients
Inference for Linear Systems with Unknown Coefficients
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Large deviation principle proven for estimators in moderate deviation zone
Parametric Statistical Inference in the Zone of Moderate Deviation Probabilities
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IV inference valid without exact structural equations
Instrumental Variable Analysis Without Structural Equations
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EMMB estimator uncovers latent intercept shifts without group labels
Robust linear regression under latent group heterogeneity
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Approximate Bayesian sampler valid for large privatized data
Large-Sample Bayesian Approximations for Privatized Data
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Odds ratio posterior invariant to margin fix iff coefficients sum to zero
Posterior Invariance of Multiplicative Contrasts under Margin Constraints in Contingency Tables
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Emergent AI abilities arise from infinite limit architecture
A Limit Theory of Foundation Models: A Mathematical Approach to Understanding Emergent Intelligence and Scaling Laws