Identification-Robust Inference With Simulation-Based Pseudo-Matching
We develop a general simulation-based inference procedure for partially specified models. Our procedure is based on matching auxiliary statistics to simulated counterparts where nuisance parameters…
Regression Analysis with Individual-Specific Patterns of Missing Covariates
It is increasingly common to collect data from heterogeneous sources in practice. Two major challenges complicate the statistical analysis of such data. First, only a small proportion of units have…
Estimating Truncated Functional Linear Models With a Nested Group Bridge Appr…
We study a scalar-on-function truncated linear regression model which assumes that the functional predictor does not influence the response when the time passes a certain cutoff point. We approach …
Locally Sparse Estimator for Functional Linear Regression Models
A new locally sparse (i.e., zero on some subregions) estimator for coefficient functions in functional linear regression models is developed based on a novel functional regularization technique cal…
Tilted Correlation Screening Learning in High-Dimensional Data Analysis
Statistical inference can be over optimistic and even misleading based on a selected model due to the uncertainty of the model selection procedure, especially in the high-dimensional data analysis.…
Covariance–Based Rational Approximations of Fractional SPDEs for Computatio…
The stochastic partial differential equation (SPDE) approach is widely used for modeling large spatial datasets. It is based on representing a Gaussian random field u on Rd as the solution of an …
Nonparametric Estimation of Search Costs for Differentiated Products : Eviden…
This article develops a method to estimate search frictions as well as preference parameters in differentiated product markets. Search costs are nonparametrically identified, which means our method…
Two-Directional Simultaneous Inference for High-Dimensional Models
This article proposes a general two-directional simultaneous inference (TOSI) framework for high-dimensional models with a manifest variable or latent variable structure, for example, high-dimensio…
Optimal One-Pass Nonparametric Estimation Under Memory Constraint
For nonparametric regression in the streaming setting, where data constantly flow in and require real-time analysis, a main challenge is that data are cleared from the computer system once processe…
Evolutionary Multitasking for Large-Scale Multiobjective Optimization
Evolutionary transfer optimization (ETO) has been becoming a hot research topic in the field of evolutionary computation, which is based on the fact that knowledge learning and transfer across the …
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