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We study the consistency of sample mean-variance portfolios of arbitrarily high dimension that are based on Bayesian or shrinkage estimation of the input parameters as well as weighted sampling. In an asymptotic setting where the number of…

Portfolio Management · Quantitative Finance 2015-05-30 Francisco Rubio , Xavier Mestre , Daniel P. Palomar

The standardized mean difference (SMD) is a widely used measure of effect size, particularly common in psychology, clinical trials, and meta-analysis involving continuous outcomes. Traditionally, under the equal variance assumption, the SMD…

Methodology · Statistics 2025-06-05 Jiandong Shi , Xiaochen Zhang , Lu Lin , Hiu Yee Kwan , Tiejun Tong

Let $Y$ be a nonnegative random variable with mean $\mu$ and finite positive variance $\sigma^2$, and let $Y^s$, defined on the same space as $Y$, have the $Y$ size biased distribution, that is, the distribution characterized by…

Probability · Mathematics 2011-06-20 Subhankar Ghosh , Larry Goldstein

In this paper, we derive closed-form exact expressions for the main statistics of the ratio of squared alpha-mu random variables, which are of interest in many scenarios for future wireless networks where generalized distributions are more…

Information Theory · Computer Science 2019-02-22 J. D. Vega Sánchez , D. P. Moya Osorio , E. E. Benitez Olivo , H. Alves , M. C. P. Paredes , L. Urquiza-Aguiar

We compute bias, variance, and approximate confidence intervals for the efficiency of a random selection process under various special conditions that occur in practical data analysis. We consider the following cases: a) the number of…

Applications · Statistics 2023-11-30 Hans Dembinski , Michael Schmelling

We derive the precise asymptotic distributional behavior of Gaussian variational approximate estimators of the parameters in a single-predictor Poisson mixed model. These results are the deepest yet obtained concerning the statistical…

Statistics Theory · Mathematics 2012-02-24 Peter Hall , Tung Pham , M. P. Wand , S. S. J. Wang

A classical approach to accurately estimating the covariance matrix \Sigma of a p-variate normal distribution is to draw a sample of size n > p and form a sample covariance matrix. However, many modern applications operate with much smaller…

Statistics Theory · Mathematics 2014-03-05 Elizaveta Levina , Roman Vershynin

We consider the jellium model of $N$ particles on a line confined in an external harmonic potential and with a pairwise one-dimensional Coulomb repulsion of strength $\alpha > 0$. Using a Coulomb gas method, we study the statistics of $s =…

Statistical Mechanics · Physics 2023-03-20 Ana Flack , Satya N. Majumdar , Gregory Schehr

Random matrix theory (RMT) successfully predicts universal statistical properties of complicated wave scattering systems in the semiclassical limit, while the random coupling model offers a complete statistical model with a simple additive…

In this paper we give a generalization of the discrete complex-valued random variable defined and investigated in \cite{ssa} and \cite{m8}. We prove the statements concerning the expressions for the excepted value and the variance of this…

Signal Processing · Electrical Eng. & Systems 2018-07-05 Romeo Meštrović

We provide finite-sample distribution approximations, that are uniform in the parameter, for inference in linear mixed models. Focus is on variances and covariances of random effects in cases where existing theory fails because their…

Statistics Theory · Mathematics 2025-07-29 Karl Oskar Ekvall , Matteo Bottai

We obtain a tight distribution-specific characterization of the sample complexity of large-margin classification with L2 regularization: We introduce the margin-adapted dimension, which is a simple function of the second order statistics of…

Machine Learning · Statistics 2013-09-19 Sivan Sabato , Nathan Srebro , Naftali Tishby

Let $\mu$ be the geometric realization on $[0,1]$ of a Gibbs measure on $\Sigma=\{0,1\}^{\mathbb{N}}$ associated with a H\"older potential. The thermodynamic and multifractal properties of $\mu$ are well known to be linked via the…

Mathematical Physics · Physics 2015-12-15 Julien Barral , Stéphane Seuret

Input variables in numerical models are often subject to several levels of uncertainty, usually modeled by probability distributions. In the context of uncertainty quantification applied to these models, studying the robustness of output…

We study asymptotic probabilities of attaining the maximum in heterogeneous Gaussian samples. In the two-group setting, the first sample has variance $1$ and size $n_1$, while the second has variance $\sigma^2>1$ and size $n_2$. We…

Probability · Mathematics 2026-05-21 Chunxu Zhang , Baiqi Miao , Tiantian Mao

The variability of temporal (or spatial) fluctuations of any variable is represented in conventional statistical theory by the relative dispersion equal to the standard deviation divided by the mean . The Relative Dispersion decreases with…

chao-dyn · Physics 2007-05-23 A. M. Selvam , Suvarna Fadnavis , S. U. Athale

We show that the spectral radius of an $N\times N$ random symmetric matrix with i.i.d. bounded centered but non-symmetrically distributed entries is bounded from above by $ 2 \*\sigma + o(N^{-6/11+\epsilon}), $ where $\sigma^2 $ is the…

Probability · Mathematics 2007-05-23 Sandrine Peche , Alexander Soshnikov

This short note proposes two additive corrections to a pair of relations published in Wan et al. in order to extend them to a small sample size condition. In particular we focus the interest on the possibility to provide an estimate to the…

Applications · Statistics 2023-10-20 Massimo Borelli

We establish finite sample bounds for the error of standard and waste-free SMC samplers. Our results cover estimates of both expectations and normalising constants of the target distributions. We consider first an arbitrary sequence of…

Computation · Statistics 2026-04-15 Yvann Le Fay , Nicolas Chopin , Matti Vihola

Several distributions and families of distributions are proposed to model skewed data, think, e.g., of skew-normal and related distributions. Lambert W random variables offer an alternative approach where, instead of constructing a new…

Methodology · Statistics 2023-10-17 Meelis Käärik , Anne Selart , Tuuli Puhkim , Liivika Tee
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