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Every paper Pith has read. Search by title, abstract, or pith.
883 papers in stat.TH · page 17
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Lipschitz regression reduces to isotonic plus linear
From Isotonic to Lipschitz Regression: A New Interpolative Perspective on Shape-restricted Estimation
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Pathwise estimator recovers volatility roughness from discrete integrated variance
Estimating the roughness exponent of stochastic volatility from discrete observations of the integrated variance
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Proxy models cut fits in changepoint detection
Reliever: Relieving the Burden of Costly Model Fits for Changepoint Detection
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Generic linear concentration models hit ML threshold at dimension count
Maximum likelihood thresholds of generic linear concentration models
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Optimal infinite-horizon estimator distributions reduce to simple form
Optimal distributions for randomized unbiased estimators with an infinite horizon and an adaptive algorithm
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The paper defines a new resilience metric for supply chains as the maximum supplier…
Structural Measures of Resilience for Supply Chains
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Sampling rates can match or exceed optimization rates
Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation
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Axiom from uniform data selects Rényi entropy
Learn your entropy from informative data: an axiom ensuring the consistent identification of generalized entropies
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MLE recovers exact communities in dependent Gaussian mixtures
Exact Recovery of Community Detection in dependent Gaussian Mixture Models
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FCS converges with normal inverse-gamma priors in linear models
Joint distribution properties of Fully Conditional Specification under the normal linear model with normal inverse-gamma priors
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Beta-binomial priors test all group equalities at once
Flexible Bayesian Multiple Comparison Adjustment Using Dirichlet Process and Beta-Binomial Model Priors
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Covariance subspaces detect vector field anomalies without distribution assumptions
Distribution-Free Stochastic Analysis and Robust Multilevel Vector Field Anomaly Detection
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Proximal operators deliver closed-form asymptotics for penalized estimators
Proximal Estimation and Inference
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f-divergences relax moment conditions for PAC-Bayes bounds
Change of measure through the Legendre transform
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Possibilistic IMs match oracle reliability in decisions
Decision-making with possibilistic inferential models
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Random-matrix flows converge to low-dimensional stochastic processes
The high-dimensional asymptotics of first order methods with random data
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AD-HMC converges geometrically with asymmetrical momenta
Hamiltonian Monte Carlo with Asymmetrical Momentum Distributions
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New MIP estimator solves sparse PCA for 20,000 features
Sparse PCA: A New Scalable Estimator Based On Integer Programming
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Wrap any model in 10 lines, get guaranteed coverage
A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
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Thompson sampling limits coincide across models when gaps shrink
Diffusion Approximations for Thompson Sampling in the Small Gap Regime
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CME sample estimators converge at explicit rates even when misspecified
Sobolev Norm Learning Rates for Conditional Mean Embeddings
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Synthetic likelihood posteriors turn multimodal under misspecification
Synthetic likelihood in misspecified models
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Nonstationarity inflates LRV estimates and distorts HAR tests
Theory of Low Frequency Contamination from Nonstationarity and Misspecification: Consequences for HAR Inference
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Generative model jointly fits QQ responses using predictor dependencies
A Generative Approach to Joint Modeling of Quantitative and Qualitative Responses
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Word subsequence counts admit explicit spectral decomposition
Spectral Analysis of Word Statistics
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All Block Maxima estimator achieves lowest variance among BM methods
All Block Maxima method for estimating the extreme value index
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Fat truncation enables efficient learning of Boolean products
Efficient Parameter Estimation of Truncated Boolean Product Distributions
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Influence parameter directs information flow in modular models
Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of components
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Low-degree likelihood ratio predicts runtime for inference tasks
Notes on Computational Hardness of Hypothesis Testing: Predictions using the Low-Degree Likelihood Ratio
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Transform of Pearson's R removes leading normal error for any alpha
An asymptotically optimal transform of Pearson's correlation statistic
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Distance threshold picks duplex mode to bound local delay in HetNets
Delay Analysis in Full-Duplex Heterogeneous Cellular Networks
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SEIR Markov chains support complete MLE via EM
Complete maximum likelihood estimation for SEIR epidemic models: theoretical development
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Node clustering controls FDR while maximizing true edge discoveries
Graph inference with clustering and false discovery rate control
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Skew-normal mixtures generate wide skewness and asymmetric tails
Exploring the Distributional Properties of the Non-Gaussian Random Field Models
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Penalty conditions make quasi-likelihood selection consistent for causal series
Consistent model selection criteria and goodness-of-fit test for affine causal processes
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Stochastic Tverberg theorems bound random hull intersections
Stochastic Tverberg theorems and their applications in multi-class logistic regression, data separability, and centerpoints of data
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Conditional probability defined in Renyi spaces
Conditional probability in Renyi spaces
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Overlapping blocks lower variance in multivariate extreme-value estimators
Multiple block sizes and overlapping blocks for multivariate time series extremes
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Posteriors on MDP dynamics converge at explicit rates
Convergence Rates of Posterior Distributions in Markov Decision Process
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GRAMPA recovers exact matchings in correlated ER graphs
Spectral Graph Matching and Regularized Quadratic Relaxations II: Erd\H{o}s-R\'enyi Graphs and Universality
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GRAMPA recovers exact graph matchings at noise level 1/log n
Spectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model
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Domain compression trades shared randomness for fewer samples in distributed tests
Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit
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Bootstrap approximates variance of randomized ensemble predictions
Estimating the Algorithmic Variance of Randomized Ensembles via the Bootstrap
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Held-out adjustment balances quantiles across groups at sqrt(n) rate
Fair quantile regression
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Data-driven estimator matches convex hull rates for r-convex sets
Extent of occurrence reconstruction using a new data-driven support estimator
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Local linear beats local constant for scalar-on-function regression
Scalar-on-function local linear regression and beyond
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Four central moments bound real matrix eigenvalue spreads
Bounds on Spreads of Matrices related to Fourth Central Moment. II
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AMP tracks SLOPE solution exactly in large limit
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing
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Genealogies and locations in populations are dual
Stochastic Evolution of spatial populations: From configurations to genealogies and back