[1] Confidence intervals for low dimensional parameters in high dimensional linear models

[2] ComNet: Combinational Neural Network for Object Detection in UAV-Borne Thermal Images

[3] Local linear regression smoothers and their minimax efficiencies

[4] The elements of financial econometrics

[5] A Path-Integral Approach to Bayesian Inference for Inverse Problems Using the Semiclassical Approximation

[6] Lithium-ion battery remaining useful life estimation based on nonlinear ar model combined with degradation feature

[7] Rerandomization Strategies for Balancing Covariates Using Pre-Experimental Longitudinal Data

[8] Virus classification in 60-dimensional protein space

[9] General forms of finite population central limit theorems with applications to causal inference

[10] On consistency and sparsity for sliced inverse regression in high dimensions

[11] Sparse Sliced Inverse Regression for High Dimensional Data

[12] Plug-in L2-upper error bounds in deconvolution, for a mixing density estimate in Rd and for its derivatives, via the L1-error for the mixture

[13] Large Covariance Estimation by Thresholding Principal Orthogonal Complements

[14] A study of variable bandwidth selection for local polynomial regression

[15] Inference in Experiments Conditional on Observed Imbalances in Covariates

[16] Asymptotic Inference for Optimal Rerandomization Designs

[17] Minimization and parameter estimation for seminorm regularization models with I -divergence constraints

[18] Distributed testing and estimation under sparse high dimensional models

[19] Statistical guarantees for the EM algorithm: From population to sample-based analysis

[20] Multivariate varying coefficient model for functional responses

[21] On optimal rerandomization designs

[22] Two Dimensional Yau-Hausdorff Distance with Applications on Comparison of DNA and Protein Sequences

[23] Association Pattern Discovery via Theme Dictionary Models

[24] Signed Support Recovery for Single Index Models in High-Dimensions

[25] Limiting distribution of the sample canonical correlation coefficients of high-dimensional random vectors

[26] Quantile Regression for Analyzing Heterogeneity in Ultra-High Dimension

[27] Sparse PCA: Optimal rates and adaptive estimation

[28] Optimal bandwidth selection for local linear regression

[29] Feature Screening via Distance Correlation Learning

[30] Optimal subspace estimation using overidentifying vectors via generalized method of moments

[31] On the Unsupervised Analysis of Domain-Specific Chinese Texts

[32] Variable selection in linear mixed effects models

[33] Sample canonical correlation coefficients of high-dimensional random vectors with finite rank correlations

[34] Tracy-Widom distribution for the edge eigenvalues of Gram type random matrices

[35] A useful variant of the Davis--Kahan theorem for statisticians.

[36] The ZD-GARCH model: A new way to study heteroscedasticity

[37] Testability of high-dimensional linear models with non-sparse structures

[38] Asymptotics of empirical eigenstructure for high dimensional spiked covariance

[39] On the optimality of sliced inverse regression in high dimensions

[40] Calibrating nonconvex penalized regression in ultra-high dimension

[41] Proper holomorphic embeddings of finitely connected planar domains into ℂ^{$n$}

[42] New local estimation procedure for a non-parametric regression function for longitudinal data

[43] Necessary and sufficient conditions for consistent root reconstruction in Markov models on trees

[44] Asymptotics For High Dimensional Regression M-Estimates: Fixed Design Results

[45] Robust principal component analysis for functional data

[46] Spot volatility estimation for high-frequency data

[47] Minimax estimation of a bounded squared mean

[48] Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems

[49] Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis

[50] Evolutionary dynamics on any population structure

[51] Panning for gold:‘model-X’ knockoffs for high dimensional controlled variable selection

[52] Tensor Methods for Additive Index Models under Discordance and Heterogeneity

[53] Time-dependent diffusion models for term structure dynamics

[54] Variable bandwidth and local linear regression smoothers

[55] Structured volatility matrix estimation for non-synchronized high-frequency financial data

[56] Distributed estimation of principal eigenspaces

[57] Profile likelihood inferences on semiparametric varying-coefficient partially linear models

[58] Fast community detection by SCORE

[59] Nonparametric Screening under Conditional Strictly Convex Loss for Ultrahigh Dimensional Sparse Data

[60] Rate-optimal perturbation bounds for singular subspaces with applications to high-dimensional statistics

[61] Data clustering based on Langevin annealing with a self-consistent potential.

[62] Edge statistics of large dimensional deformed rectangular matrices

[63] Factor GARCH-It models for high-frequency data with application to large volatility matrix prediction

[64] Coauthorship and citation networks for statisticians

[65] Lectures on the nearest neighbor method

[66] Generalised likelihood ratio tests for spectral density

[67] Nonparametric regression with errors in variables

[68] Estimation of conditional densities and sensitivity measures in nonlinear dynamical systems

[69] Strong oracle optimality of folded concave penalized estimation

[70] Nonparametric independence screening in sparse ultra-high-dimensional additive models

[71] On model selection from a finite family of possibly misspecified time series models

[72] Variable selection for Cox's proportional hazards model and frailty model

[73] On the optimal rates of convergence for nonparametric deconvolution problems

[74] Vast portfolio selection with gross-exposure constraints

[75] QUADRO: A supervised dimension reduction method via Rayleigh quotient optimization

[76] Multivariate regression estimation with errors-in-variables: asymptotic normality for mixing processes

[77] Supplementary material to “Panning for gold: Model-X knock- offs for high-dimensional controlled variable selection”

[78] Factor-adjusted regularized model selection

[79] Large panel test of factor pricing models

[80] Heterogeneity adjustment with applications to graphical model inference

[81] Estimating False Discovery Proportion under Arbitrary Covariance Dependence

[82] Partially linear hazard regression for multivariate survival data

[83] Large dimensional covariance matrix estimation using a factor model

[84] Variable selection for multivariate failure time data

[85] Estimating sparse precision matrix: optimal rates of convergence and adaptive estimation

[86] G-sup: a clustering algorithm for cryo-electron microscopy images of asymmetric particles

[87] An \ell_{\infty} Eigenvector Perturbation Bound and Its Application to Robust Covariance Estimation

[88] Bootstrap methods: A guide for practitioners and researchers

[89] When everyone misses on the same side: Debiased earnings surprises and stock returns

[90] Minimax efficiency of local polynomial fit estimators at boundaries

[91] Variance estimation using refitted crossvalidation in ultrahigh dimensional regression

[92] Model selection for high-dimensional linear regression with dependent observations

[93] Optimal global rates of convergence for nonparametric deconvolution problem

[94] Robust inference of risks of large portfolios

[95] Deconvolution with supersmooth distributions

[96] Estimation of high dimensional mean regression in the absence of symmetry and light tail assumptions

[97] Power Enhancement in HighDimensional CrossSectional Tests

[98] Some problems on the estimation of unimodal densities

[99] Diffusion in a continuum model of self-propelled particles with alignment interaction

[100] Semiparametric estimation of covariance matrixes for longitudinal data

[101] Analysis of longitudinal data with semiparametric estimation of covariance function

[102] Bernstein's inequality for general Markov chains

[103] Lecture 3: Fourth Order BSS Method

[104] Statistical estimation in varying coefficient models

[105] A Projection-based Conditional Dependence Measure with Applications to High-dimensional Undirected Graphical Models

[106] Sufficient forecasting using factor models

[107] Multiple testing via fdr for large scale imaging data

[108] Dynamic nonparametric filtering with application to volatility estimation

[109] Propagation of singularities in the solutions to the Boltzmann equation near equilibrium

[110] A design-adaptive local polynomial estimator for the errors-in-variables problem

[111] FARM-Test: Factoradjusted robust multiple testing with false discovery control

[112] Correcting In-Sample Optimism Bias: Realized Volatility of Large Optimal Portfolios

[113] Precision matrix estimation in high dimensional gaussian graphical models with faster rates

[114] Spatially varying coefficient model for neuroimaging data with jump discontinuities

[115] Sure independence screening in generalized linear models with NP-dimensionality

[116] Structured correlation detection with application to colocalization analysis in dual-channel fluorescence microscopic imaging

[117] High dimensional covariance matrix estimation using a factor model

[118] Testing and detecting jumps based on a discretely observed process

[119] Semiparametric estimation of Value at Risk

[120] Discrete discrepancy and its application in experimental design

[121] Enhanced diffusivity in perturbed senile reinforced random walk models

[122] Regularity properties of high-dimensional covariate matrices

[123] Statistical challenges with high dimensionality: Feature selection in knowledge discovery

[124] The leverage effect puzzle: Disentangling sources of bias at high frequency

[125] Asymptotics of empirical eigen-structure for ultra-high dimensional spiked covariance model

[126] Robust covariance estimation for approximate factor models

[127] Adaptively local 1-dimensional subproblems

[128] A semiparametric model for cluster data

[129] Adaptive Huber Regression on Markov-dependent Data

[130] Correction to strong oracle optimality of folded concave penalized estimation

[131] When Everyone Misses on the Same Side: Robust Measures of Earnings Surprises and Stock Returns

[132] Nonconcave penalized likelihood with a diverging number of parameters

[133] Assessing prediction error of nonparametric regression and classification under Bregman divergence

[134] Goodness-of-fit tests for parametric regression models

[135] Semiparametric estimation of value-at-risk

[136] Generalized likelihood ratio tests for spectral density

[137] Multiple testing via FDRl for large scale imaging data

[138] FarmTest: Factor-adjusted robust multiple testing with approximate false discovery control

[139] Hazard models with varying coefficients for multivariate failure time data

[140] Design-adaptive minimax local linear regression for longitudinal/clustered data

[141] Residual diffusivity in elephant random walk models with stops

[142] On the estimation of quadratic functionals

[143] Statistical analysis of big data on pharmacogenomics

[144] Multi-Agent Inference in Social Networks: A Finite Population Approach

[145] Covariance assisted screening and estimation

[146] Efficient estimation and inferences for varying-coefficient models

[147] Nonparametric tests of the Markov hypothesis in continuous-time models

[148] Nonparametric Mixture of Regression Models

[149] Best possible constant for bandwidth selection

[150] Principal component analysis for big data

[151] Variable selection via penalized likelihood

[152] Regularization for Coxs proportional hazards model with NP-dimensionality

[153] Test of significance when data are curves

[154] Estimation in additive models with highly or nonhighly correlated covariates

[155] On definitive screening designs using Paley’s conference matrices

[156] Expectation-maximization algorithm with local adaptivity

[157] Local polynomial kernel regression for generalized linear models and quasi-likelihood functions

[158] Nonconcave penalized likelihood with NP-dimensionality

[159] Statistical analysis of a semilinear hyperbolic system advected by a white in time random velocity field

[160] Ultrahigh dimensional feature selection: beyond the linear model

[161] Nonlinearly constrained MRFs: exploring the intrinsic dimensions of higher-order cliques

[162] Gaussian Fluctuation for the Number of Particles in Airy, Bessel, Sine, and Other Determinantal Random Point Fields Alexander B. Soshnikov Limiting Distributions for a

[163] Non-and semi-parametric modeling in survival analysis

[164] Comments on wavelets in statistics: A review by a. antoniadis

[165] Sparsistency and rates of convergence in large covariance matrices estimation, 2007

[166] The Leverage Effect Puzzle: Disentangling Sources of Bias at High Frequency. February 5, 2013

[167] Nonparametric independence screening in sparse ultra-high-dimensional varying coefficient models

[168] Convergence analysis of a randomly perturbed infomax algorithm for blind source separation

[169] New estimation and model selection procedures for semiparametric modeling in longitudinal data analysis

[170] Guarding against spurious discoveries in high dimensions

[171] Aggregation of nonparametric estimators for volatility matrix

[172] Deconvolution Problems in Time Series

[173] Feature augmentation via nonparametrics and selection (FANS) in high-dimensional classification

[174] Multiscale adaptive smoothing models for the hemodynamic response function in fMRI

[175] Fast implementations of nonparametric curve estimators

[176] High-frequency covariance estimates with noisy and asynchronous financial data

[177] Sieve empirical likelihood ratio tests for nonparametric functions

[178] A projection based conditional dependence measure with applications to high-dimensional undirected graphical models

[179] Rates of convergence for the pre-asymptotic substitution bandwidth selector

[180] Direct estimation of low-dimensional components in additive models

[181] Varying-coefficient functional linear regression

[182] Local quasi-likelihood with a parametric guide

[183] Local quasi-likelihood estimation with data missing at random

[184] Skewing methods for two-parameter locally parametric density estimation

[185] Bias correction and higher order kernel functions

[186] Bayesian Aggregation of Order-Based Rank Data

[187] Spectral Method and Regularized MLE Are Both Optimal for Top-K Ranking

[188] New inference concepts for analysing complex data

[189] Dynamic integration of time-and state-domain methods for volatility estimation

[190] Sieve likelihood ratio statistics and Wilks phenomenon

[191] Multi-agent inference in social networks: a finite population learning approach

[192] High dimensional semiparametric latent graphical model for mixed data

[193] Sparsistency and rates of convergence in large covariance matrix estimation

[194] Local partial-likelihood estimation for lifetime data

[195] Ultrahigh dimensional variable selection: beyond the linear model

[196] Are discoveries spurious? Distributions of maximum spurious correlations and their applications

[197] Nonparametric estimation of quadratic regression functionals

[198] An l eigenvector perturbation bound and its application to robust covariance estimation

[199] Local likelihood and local partial likelihood in hazard regression

[200] The Bivariate Lack-of-Memory Distributions

[201] Average regression surface for dependent data

[202] Estimation of functionals of sparse covariance matrices

[203] Feature Selection for Varying Coefficient Models With Ultrahigh-Dimensional Covariates

[204] Estimation of the false discovery proportion with unknown dependence

[205] Datadriven bandwidth selection in local polynomial fitting: variable bandwidth and spatial adaptation

[206] Asset allocation with gross exposure constraints for vast portfolios

[207] A cell based particle method for modeling dynamic interfaces

[208] Option pricing with model-guided nonparametric methods

[209] Modelling multivariate volatilities via conditionally uncorrelated components

[210] Control of the false discovery rate under arbitrary covariance dependence

[211] Estimating Measures of Sensitivity of Initial Values to Nonlinear Stochastic Systems with Chaos

[212] A crossvalidation method for estimating conditional densities

[213] Nonparametric function estimation involving errors-in-variables

[214] Adaptive varyingcoefficient linear models

[215] Journal of the Korean Statistical Society

[216] Projected principal component analysis in factor models

[217] Nonparametric modeling of longitudinal covariance structure in functional mapping of quantitative trait loci

[218] Embracing the blessing of dimensionality in factor models

[219] Nonparametric transition-based tests for jump diffusions

[220] Data-driven bandwidth selection in local polynomial fitting: variable bandwidth and spatial adaptation [J]

[221] Data-analytic approaches to the estimation of value-at-risk

[222] Local polynomial estimation of regression functions for mixing processes

[223] Endogeneity in ultrahigh dimension

[224] Nonparametric transition-based tests for diffusions

[225] Regularity properties for sparse regression

[226] Nonparametric inference with generalized likelihood ratio tests

[227] Onestep local quasilikelihood estimation

[228] Error variance estimation in ultrahigh-dimensional additive models

[229] Partially linear hazard regression with varying coefficients for multivariate survival data

[230] Asymptotic normality for deconvolution kernel density estimators

[231] Quasi-maximum likelihood estimation of GARCH models with heavy-tailed likelihoods