AbstractGiven a probability measure μ on Borel sigma-field of Rd, and a function f:Rd↦R, the main issue of this work is to establish inequalities of the type f(m)⩽M, where m is a median (or a deepest point in the sense explained in the paper) of μ and M is a median (or an appropriate quantile) of the measure μf=μ○f−1. For the most popular choice of halfspace depth, we prove that the Jensen's inequality holds for the class of quasi-convex and lower semi-continuous functions f. To accomplish the task, we give a sequence of results regarding the “type D depth functions” according to classification in [Y. Zuo, R. Serfling, General notions of statistical depth function, Ann. Statist. 28 (2000) 461–482], and prove several structural properties of...
Classical multivariate statistics measures the outlyingness of a point by its Mahalanobis distance f...
A refinement of the discrete Jensen’s inequality for convex functions defined on a convex subset in...
AbstractJensen's inequality f(EX) ≤ Ef(X) for the expectation of a convex function of a random varia...
We prove an analogue of Jensen's inequality, with medians instead of means. A novel definition of a ...
Jensen's inequality states for a random variable X with values in Rd and existing expectation and f...
Jensen’s inequality states for a random variable X with values in Rd and existing expectation and fo...
Abstract. We develop a new framework for the Jensen-type inequalities that allows us to deal with fu...
An inequality with respect to strictly convex/concave functions is discussed. It can be considered a...
In this thesis we introduce the halfspace median, which is one of the possibilities how to extend th...
An improvement of the Jensen inequality for convex and monotone function is given as well as variou...
A refinement and a new sharp reverse of Jensen's inequality for convex functions in terms of divided...
We study how good is Jensen's inequality, that is the discrepancy between $\int_0^1 \varphi(f(x)) \,...
In this paper we have considered a difference of Jensen’s inequality for convex functions and prove...
Inequalities lie at the heart of a great deal of mathematics.G. H. Hardy reported Harald Bohr as say...
Statistical data depth is a nonparametric tool applicable to multivariate datasets in an attempt to ...
Classical multivariate statistics measures the outlyingness of a point by its Mahalanobis distance f...
A refinement of the discrete Jensen’s inequality for convex functions defined on a convex subset in...
AbstractJensen's inequality f(EX) ≤ Ef(X) for the expectation of a convex function of a random varia...
We prove an analogue of Jensen's inequality, with medians instead of means. A novel definition of a ...
Jensen's inequality states for a random variable X with values in Rd and existing expectation and f...
Jensen’s inequality states for a random variable X with values in Rd and existing expectation and fo...
Abstract. We develop a new framework for the Jensen-type inequalities that allows us to deal with fu...
An inequality with respect to strictly convex/concave functions is discussed. It can be considered a...
In this thesis we introduce the halfspace median, which is one of the possibilities how to extend th...
An improvement of the Jensen inequality for convex and monotone function is given as well as variou...
A refinement and a new sharp reverse of Jensen's inequality for convex functions in terms of divided...
We study how good is Jensen's inequality, that is the discrepancy between $\int_0^1 \varphi(f(x)) \,...
In this paper we have considered a difference of Jensen’s inequality for convex functions and prove...
Inequalities lie at the heart of a great deal of mathematics.G. H. Hardy reported Harald Bohr as say...
Statistical data depth is a nonparametric tool applicable to multivariate datasets in an attempt to ...
Classical multivariate statistics measures the outlyingness of a point by its Mahalanobis distance f...
A refinement of the discrete Jensen’s inequality for convex functions defined on a convex subset in...
AbstractJensen's inequality f(EX) ≤ Ef(X) for the expectation of a convex function of a random varia...