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This paper deals with the asymptotic statistical properties of a class of redescending M-estimators in linear models with increasing dimension. This class is wide enough to include popular high breakdown point estimators such as…

Statistics Theory · Mathematics 2016-12-20 Ezequiel Smucler

Instrumental variable models allow us to identify a causal function between covariates $X$ and a response $Y$, even in the presence of unobserved confounding. Most of the existing estimators assume that the error term in the response $Y$…

Machine Learning · Statistics 2022-09-23 Sorawit Saengkyongam , Leonard Henckel , Niklas Pfister , Jonas Peters

We consider the problem of estimating the mean and covariance of a distribution from iid samples in $\mathbb{R}^n$, in the presence of an $\eta$ fraction of malicious noise; this is in contrast to much recent work where the noise itself is…

Data Structures and Algorithms · Computer Science 2016-08-16 Kevin A. Lai , Anup B. Rao , Santosh Vempala

We use bias-reduced estimators of high quantiles, of heavy-tailed distributions, to introduce a new estimator of the mean in the case of infinite second moment. The asymptotic normality of the proposed estimator is established and checked,…

Methodology · Statistics 2014-05-09 Brahim Brahimi , Djamel Meraghni , Abdelhakim Necir , Djabrane Yahia

We re-investigate the asymptotic properties of the traditional OLS (pooled) estimator, $\hat{\beta} _P$, in the context of cluster dependence. The present study considers various scenarios under various restrictions on the cluster sizes and…

Methodology · Statistics 2025-01-31 Subhodeep Dey , Gopal K. Basak , Samarjit Das

In this work we consider the problem of estimating a high-dimensional $p \times p$ covariance matrix $\Sigma$, given $n$ observations of confounded data with covariance $\Sigma + \Gamma \Gamma^T$, where $\Gamma$ is an unknown $p \times q$…

Methodology · Statistics 2019-12-03 Rajen D. Shah , Benjamin Frot , Gian-Andrea Thanei , Nicolai Meinshausen

We discuss a class of difference-based estimators for the autocovariance in nonparametric regression when the signal is discontinuous (change-point regression), possibly highly fluctuating, and the errors form a stationary $m$-dependent…

Methodology · Statistics 2016-08-09 Inder Tecuapetla-Gómez , Axel Munk

We introduce a new method for estimating the mean of an outcome variable within groups when researchers only observe the average of the outcome and group indicators across a set of aggregation units, such as geographical areas. Existing…

Methodology · Statistics 2026-05-01 Cory McCartan , Shiro Kuriwaki

U-statistics constitute a large class of estimators, generalizing the empirical mean of a random variable $X$ to sums over every $k$-tuple of distinct observations of $X$. They may be used to estimate a regular functional $\theta(P_{X})$ of…

Statistics Theory · Mathematics 2019-03-27 Alexis Derumigny

We study regression discontinuity designs with the use of additional covariates for estimation of the average treatment effect. We provide a detailed proof of asymptotic normality of the covariate-adjusted estimator under minimal…

Statistics Theory · Mathematics 2023-10-16 Patrick Kramer , Alexander Kreiß

To measure the degree of agreement between two observers that independently classify $n$ subjects within $K$ categories, it is common to use different kappa type coefficients, the most common of which is the $\kappa_C$ coefficient (Cohen's…

Statistics Theory · Mathematics 2026-02-24 A. Martín Andrés , M. Álvarez Hernández

The distribution functions of the matricvariate beta type I and II distributions are studied under real normed division algebras. The unified approach for real, complex, quaternions and octonions, also considers general properties and…

Statistics Theory · Mathematics 2024-09-27 José A. Díaz-García , Francisco J. Caro-Lopera

In this paper we study covariance estimation with missing data. We consider missing data mechanisms that can be independent of the data, or have a time varying dependency. Additionally, observed variables may have arbitrary (non uniform)…

Statistics Theory · Mathematics 2021-06-17 Eduardo Pavez , Antonio Ortega

This paper deals with testing for nondegenerate normality of a $d$-variate random vector $X$ based on a random sample $X_1,\ldots,X_n$ of $X$. The rationale of the test is that the characteristic function $\psi(t) = \exp(-\|t\|^2/2)$ of the…

Statistics Theory · Mathematics 2019-11-26 Philip Dörr , Bruno Ebner , Norbert Henze

The main theorem in Judge and Mittelhammer [Judge, G. G., and Mittelhammer, R. (2004), A Semiparametric Basis for Combining Estimation Problems under Quadratic Loss; JASA, 99, 466, 479--487] stipulates that, in the context of nonzero…

Methodology · Statistics 2015-09-07 Severien Nkurunziza

We study the problem of estimation of the value N_gamma(\theta) = sum(i=1)^d |\theta_i|^gamma for 0 < gamma <= 1 based on the observations y_i = \theta_i + \epsilon\xi_i, i = 1,...,d, where \theta = (\theta_1,...,\theta_d) are unknown…

Statistics Theory · Mathematics 2019-10-08 Olivier Collier , Laëtitia Comminges , Alexandre B. Tsybakov

We present new M-estimators of the mean and variance of real valued random variables, based on PAC-Bayes bounds. We analyze the non-asymptotic minimax properties of the deviations of those estimators for sample distributions having either a…

Statistics Theory · Mathematics 2011-08-15 Olivier Catoni

Using log canonical thresholds and basis divisors Fujita--Odaka introduced purely algebro-geometric invariants $\delta_m$ whose limit in $m$ is now known to characterize uniform K-stability on a Fano variety. As shown by Blum-Jonsson this…

Differential Geometry · Mathematics 2024-11-20 Yanir A. Rubinstein , Gang Tian , Kewei Zhang

In this article, we propose a new class of consistent tests for $p$-variate normality. These tests are based on the characterization of the standard multivariate normal distribution, that the Hessian of the corresponding cumulant generating…

Methodology · Statistics 2023-03-22 Kwun Chuen Gary Chan , Hok Kan Ling , Chuan-Fa Tang , Sheung Chi Phillip Yam

We study the tail bound of the emperical covariance of multivariate normal distribution. Following the work of (Gittens & Tropp, 2011), we provide a tail bound with a small constant.

Statistics Theory · Mathematics 2012-12-27 Shenghuo Zhu
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