Forthcoming AISM Papers

Correction to: Methods for generating new families of continuous univariate distributions

Compound empirical Bayes interval estimation

Simultaneously sparse and low-rank matrix estimation via l₁-norm and nonconvex regularization

Debiased group lasso for multiple compositional data

Rate of convergence of over-parametrized deep neural network regression estimates learned by stochastic gradient descent

Continuous logistic Gaussian random measure fields for spatial distributional modelling

Building a theoretical foundation for combining negative controls and replicates

Generalized high-dimensional tensor learning with nuclear norm regularization

Combining variable screening methods for model averaging in high-dimensional data analysis

An information criterion for robust estimation with unnormalized statistical models

Threshold detection under a semiparametric regression model

Estimation of bivariate minimum information dependence models using the density-ratio framework

On the differentiability of ϕ-projections in the discrete finite case

Bayesian group regularization in generalized linear models with a continuous spike-and-slab prior

The space of positive transition measures on a Markov chain

Adaptive thresholds for monitoring and screening in imbalanced samples: optimality and boosting sensitivity

Analysis of a truncated kernel ridge regression estimator based on two varying probability measures

Methods for generating new families of continuous univariate distributions

Infill asymptotics for logistic regression estimators for parameters of the intensity function of spatial point processes

Thresholded Lasso for high dimensional variable selection

Estimation and variable selection of higher-order spatial autoregressive functional coefficient model with endogenous covariates and diverging dimension

Limit theorems for self-similar symmetric stable moving average processes: a study with p-variations

Discussion of "Estimation of bivariate minimum information dependence models using the density-ratio framework"

Discussion on "Estimation of bivariate minimum information dependence models using the density-ratio framework"

Asymptotic properties of empirical likelihood MLE for joint modeling right censored survival data and intensive longitudinal covariates

Non parametric regression function estimation in presence of common noise

Nonparametric estimation of hitting-time variance

Disentangling endogeneity and exogeneity in cryptocurrency markets using the modulated renewal Hawkes process with marks

Quasi-likelihood analysis for adaptive estimation of a degenerate diffusion process

Multi-arm Treatment Comparison in Optimal Response-adaptive Designs Controlling FWER-I and FWER-II

On robustness of spectral Rényi divergence

Debiased inference in errors-in-variables problems with non-Gaussian measurement error

Robust estimation and model selection for the controlled direct effect with unmeasured mediator--outcome confounders

A Lower Bound for Estimating Frechet Means

Confident Grouping in Singular Spectrum Analysis via Multiple Testing

Nadaraya-Watson Type Estimator of the Transition Density Function for Diffusion Processes

Rejoinder to the discussion of "Estimation of bivariate minimum information dependence models using the density-ratio framework"

A three-stage sequential sampling procedure for comparing linear parametric functions of two multiple linear regression models with standardized predictors: illustration using Boston housing data

Learning of deep convolutional network image classifiers via stochastic gradient descent and over-parametrization

Infill Asymptotics for Closed-Form Alternatives to Maximum Likelihood Estimators of Covariance Parameters in the Ornstein-Uhlenbeck Fields

Convergence of systematic-scan and random-scan Gibbs samplers for bivariate discrete conditional distributions

Residual Analysis in the Generalized Growth Curve Model

Polyspectral Factorization