real life data sets have been analyzed for illustrative purposes. The objective of this paper is to estimate the parameters of the model from both frequentist and Bayesian perspective and to develop a …

In arbitrary vector spaces, we will be able to develop a generalization of the directional derivative (called the Gateaux differential) and of the gradient (called the Frechet derivative).

ises with hints. The basic definition is that a Fr ́echet space is a complete metric space with the metric defined by a family of seminorms, a seminorm being a slightly weaker v. rsion of a norm. An …

variable selection for global Frechet regression. In this paper, we propose a novel variable selection approach that is shown to work for global Frechet regression by extending the ridge selection …

between P and Q, denoted by H(P, Q), is max{h(P, Q), h(Q, P)}. Intuitively, the function h(P, Q) finds the point p ∈ P that is farthest from any point in Q and measures the distance from p to its nearest …

imulations for different kinds of random objects. We illustrate the proposed methods with data on mortality profiles of various 20 countries and resting.

ases of the so-called generalized extreme value (GEV) distribution. The Fréchet distribution is named after French mathematician Maurice René Fréchet, who developed it in the 1920s as a maximum...