Zobrazeno 1 - 10
of 297
pro vyhledávání: '"Cattaneo, Matias D."'
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 consistency for convex and non-convex objective functions; (ii) optimal
Externí odkaz:
http://arxiv.org/abs/2409.05715
Binned scatter plots are a powerful statistical tool for empirical work in the social, behavioral, and biomedical sciences. Available methods rely on a quantile-based partitioning estimator of the conditional mean regression function to primarily con
Externí odkaz:
http://arxiv.org/abs/2407.15276
Autor:
Cattaneo, Matias D., Yu, Ruiqi Rae
This paper presents new uniform Gaussian strong approximations for empirical processes indexed by classes of functions based on $d$-variate random vectors ($d\geq1$). First, a uniform Gaussian strong approximation is established for general empirical
Externí odkaz:
http://arxiv.org/abs/2406.04191
Autor:
Cattaneo, Matias D., Titiunik, Rocio
In his 2022 IMS Medallion Lecture delivered at the Joint Statistical Meetings, Prof. Dylan S. Small eloquently advocated for the use of protocols in observational studies. We discuss his proposal and, inspired by his ideas, we develop a protocol for
Externí odkaz:
http://arxiv.org/abs/2402.11640
In two influential contributions, Rosenbaum (2005, 2020) advocated for using the distances between component-wise ranks, instead of the original data values, to measure covariate similarity when constructing matching estimators of average treatment e
Externí odkaz:
http://arxiv.org/abs/2312.07683
Random forests are popular methods for regression and classification analysis, and many different variants have been proposed in recent years. One interesting example is the Mondrian random forest, in which the underlying constituent trees are constr
Externí odkaz:
http://arxiv.org/abs/2310.09702
In previous literature, backward error analysis was used to find ordinary differential equations (ODEs) approximating the gradient descent trajectory. It was found that finite step sizes implicitly regularize solutions because terms appearing in the
Externí odkaz:
http://arxiv.org/abs/2309.00079
Barseghyan and Molinari (2023) give sufficient conditions for semi-nonparametric point identification of parameters of interest in a mixture model of decision-making under risk, allowing for unobserved heterogeneity in utility functions and limited c
Externí odkaz:
http://arxiv.org/abs/2305.10934
Westling and Carone (2020) proposed a framework for studying the large sample distributional properties of generalized Grenander-type estimators, a versatile class of nonparametric estimators of monotone functions. The limiting distribution of those
Externí odkaz:
http://arxiv.org/abs/2303.13598