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20182024
most citedOptimal Estimation of Large-Dimensional Nonlinear Factor Models

1 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

math.ST2024

Uniform Estimation and Inference for Nonparametric Partitioning-Based M-Estimators

Matias D. Cattaneo, Yingjie Feng, Boris Shigida

This paper presents uniform estimation and inference theory for a large class of nonparametric partitioning-based M-estimators. The main theoretical results include: (i) uniform co…

stat.ME2024★ 1 cited

Nonlinear Binscatter Methods

Matias D. Cattaneo, Richard K. Crump, Max H. Farrell +1

Binscatters are a powerful tool for empirical work in the social, behavioral, and biomedical sciences. Available tools rely on least squares estimation of the conditional mean. We…

math.ST2023★ 1 cited

Optimal Estimation of Large-Dimensional Nonlinear Factor Models

Yingjie Feng

This paper studies optimal estimation of large-dimensional nonlinear factor models. The key challenge is that the observed variables are possibly nonlinear functions of some latent…

stat.CO2019

lspartition: Partitioning-Based Least Squares Regression

Matias D. Cattaneo, Max H. Farrell, Yingjie Feng

Nonparametric partitioning-based least squares regression is an important tool in empirical work. Common examples include regressions based on splines, wavelets, and piecewise poly…

math.ST2018

Large Sample Properties of Partitioning-Based Series Estimators

Matias D. Cattaneo, Max H. Farrell, Yingjie Feng

We present large sample results for partitioning-based least squares nonparametric regression, a popular method for approximating conditional expectation functions in statistics, e…