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pro vyhledávání: '"BROWN, LAWRENCE D."'
This article discusses estimation of a multivariate normal mean based on heteroscedastic observations. Under heteroscedasticity, estimators shrinking more on the coordinates with larger variances, seem desirable. Although they are not necessarily min
Externí odkaz:
http://arxiv.org/abs/2206.10856
Autor:
Wolpert, Robert L, Brown, Lawrence D.
We prove a complete class theorem that characterizes \emph{all} stationary time reversible Markov processes whose finite dimensional marginal distributions (of all orders) are infinitely divisible. Aside from two degenerate cases (iid and constant),
Externí odkaz:
http://arxiv.org/abs/2105.14591
Least squares linear regression is one of the oldest and widely used data analysis tools. Although the theoretical analysis of the ordinary least squares (OLS) estimator is as old, several fundamental questions are yet to be answered. Suppose regress
Externí odkaz:
http://arxiv.org/abs/1910.06386
Ordinary least squares (OLS) linear regression is one of the most basic statistical techniques for data analysis. In the main stream literature and the statistical education, the study of linear regression is typically restricted to the case where th
Externí odkaz:
http://arxiv.org/abs/1809.10538
Construction of valid statistical inference for estimators based on data-driven selection has received a lot of attention in the recent times. Berk et al. (2013) is possibly the first work to provide valid inference for Gaussian homoscedastic linear
Externí odkaz:
http://arxiv.org/abs/1806.04119
For the last two decades, high-dimensional data and methods have proliferated throughout the literature. Yet, the classical technique of linear regression has not lost its usefulness in applications. In fact, many high-dimensional estimation techniqu
Externí odkaz:
http://arxiv.org/abs/1802.05801
Autor:
SPARER, MICHAEL S.1 mss16@cumc.columbia.edu, BROWN, LAWRENCE D.1
Publikováno v:
Milbank Quarterly. Sep2023, Vol. 101 Issue 3, p815-840. 26p.
Autor:
Kuchibhotla, Arun K., Brown, Lawrence D., Buja, Andreas, Cai, Junhui, George, Edward I., Zhao, Linda H.
Publikováno v:
The Annals of Statistics, 2020 Oct 01. 48(5), 2953-2981.
Externí odkaz:
https://www.jstor.org/stable/27028728