Hasil untuk "math.ST"

Victory Idowu

Archimedean copulas are a popular type of copulas in which a variant of the Archimedean axiom apply. We provide a topological proof of the Archimedean Axiom which is applicable for non-continuous distribution functions.

Guanyi Wu

This article present a method of mutual transformation between count model and composition model. Offer the mathematical view of classical radio and log-radio in compositional data analysis and expand the idea of mixture model of counts data to the case of compositional data.

Jiwoong Kim

We propose a minimum distance estimation of a rate parameter of some probability distributions. This paper discusses asymptotic properties of the resulting estimator. Next, we compare the proposed estimator with other estimators.

Yuzo Maruyama

The original Hotelling-Solomons inequality indicates that an upper bound of |mean - median|/(standard deviation) is 1. In this note, we find a new bound depending on the sample size, which is strictly smaller than 1.

Martin Wahl

We establish non-asymptotic lower bounds for the estimation of principal subspaces. As applications, we obtain new results for the excess risk of principal component analysis and the matrix denoising problem.

Yejiong Zhu, Hao Chen

We provide sufficient conditions for the asymptotic normality of the generalized correlation coefficient $\sum a_{ij}b_{ij}$ under the permutation null distribution when $a_{ij}$'s are symmetric and $b_{ij}$'s are symmetric.

Mikhail Ermakov

For Kolmogorov test we find natural conditions of uniform consistency of sets of alternatives approaching to hypothesis. Sets of alternatives can be defined both in terms of distribution functions and in terms of densities.

Iosif Pinelis

Closed-form expressions for the distributions of the order statistics on the spacings between order statistics for the uniform distribution are obtained. This generalizes a result by Fisher concerning tests of significance in the harmonic analysis of a series.

Ismaël Castillo

Discussion of "Frequentist coverage of adaptive nonparametric Bayesian credible sets" by Szabó, van der Vaart and van Zanten [arXiv:1310.4489v5].

Judith Rousseau

Discussion of "Frequentist coverage of adaptive nonparametric Bayesian credible sets" by Szabó, van der Vaart and van Zanten [arXiv:1310.4489v5].

Xia Shen, Zheng Ning, Yudi Pawitan

Derived here is a single regression coefficient equivalent to Pillai's trace statistic in multivariate analysis of variance.

Stephen Montgomery-Smith, T. Schürmann

We introduce unbiased estimators for the Shannon entropy and the class number, in the situation that we are able to take sequences of independent samples of arbitrary length.

Nancy Reid

I review the classical theory of likelihood based inference and consider how it is being extended and developed for use in complex models and sampling schemes.

Paulo C. Marques F

We describe briefly in this note a procedure for consistently estimating the marginal likelihood of a statistical model through a sample from the posterior distribution of the model parameters.

Yindeng Jiang, Michael D. Perlman

For a bivariate random vector (X,Y), symmetry conditions are presented that yield stochastic orderings among |X|, |Y|, |max(X,Y)|, and | min(X, Y)|. Partial extensions of these results for multivariate random vectors (X1,...,Xn) are also given.

Ouerdia Arkoun

We constuct a sequential adaptive procedure for estimating the autoregressive function at a given point in nonparametric autoregression models with Gaussian noise. We make use of the sequential kernel estimators. The optimal adaptive convergence rate is given as well as the upper bound for the minimax risk.

Jean-François Coeurjolly

We obtain a Bahadur representation for sample quantiles of nonlinear functional of Gaussian sequences with correlation function decreasing as $k^{-α}$ for some $α> 0$. This representation is derived under a mimimal assumption.

Werner Hurlimann

On the occasion of the 125-th anniversary of Newcomb's paper, a bibliography of academic work related to Benford's law from its year of origin 1881 to 2006 has been compiled.

R. Averkamp, C. Houdré

Unbiased risk estimation, à la Stein, is studied for infinitely divisible laws with finite second moment.

Bert van Es

We construct a density estimator and an estimator of the distribution function in the uniform deconvolution model. The estimators are based on inversion formulas and kernel estimators of the density of the observations and its derivative. Asymptotic normality and the asymptotic biases are derived.