Results 11 to 20 of about 143,710 (291)

Learning with Stochastic Orders

open access: yesCoRR, 2022
Code available at https://github.com/yair-schiff/stochastic-orders ...
Carles Domingo-Enrich   +2 more
openaire   +3 more sources

Modeling Extreme Values with Alpha Power Inverse Pareto Distribution

open access: yesMeasurement Science Review, 2023
The study focuses on the development of a new probability distribution with applications to extreme values. The distribution is proposed by incorporating an additional parameter into the inverse Pareto distribution using the α-Power Transformation ...
Ihtisham Shumaila   +5 more
doaj   +1 more source

A New Stochastic Order of Multivariate Distributions: Application in the Study of Reliability of Bridges Affected by Earthquakes

open access: yesMathematics, 2022
In this article, we introduce and study a new stochastic order of multivariate distributions, namely, the conditional likelihood ratio order. The proposed order and other stochastic orders are analyzed in the case of a bivariate exponential distributions
Luigi-Ionut Catana, Vasile Preda
doaj   +1 more source

Second-order stochastic comparisons of order statistics [PDF]

open access: yesStatistics, 2021
We study the problem of comparing ageing patterns of the lifetime of k-out-of-n systems. Mathematically, this reduces to being able to decide about a stochastic ordering relationship between different order statistics. We discuss such relationships with respect to second-order stochastic dominance, obtaining characterizations through the verification ...
Lando, Tommaso   +2 more
openaire   +3 more sources

Ohlin and Levin–Stečkin-Type Results for Strongly Convex Functions

open access: yesAnnales Mathematicae Silesianae, 2020
Counterparts of the Ohlin and Levin–Stečkin theorems for strongly convex functions are proved. An application of these results to obtain some known inequalities related with strongly convex functions in an alternative and unified way is presented.
Nikodem Kazimierz, Rajba Teresa
doaj   +1 more source

Stochastic permutation ordering watershed [PDF]

open access: yes2021 29th European Signal Processing Conference (EUSIPCO), 2021
The stochastic watershed is a morphological approach to segmentation that repeats the application of a seeded watershed from series of uniform random markers. The obtained watershed boundaries are combined to construct a probability density function. We propose an alternative approach called stochastic permutation ordering watershed.
openaire   +2 more sources

The Marshall-Olkin Odd Burr III-G Family: Theory, Estimation, and Engineering Applications

open access: yesIEEE Access, 2021
We propose a new flexible class called the Marshall-Olkin odd Burr III family for generating continuous distributions and derive some of its statistical properties.
Ahmed Z. Afify   +5 more
doaj   +1 more source

RELATIONS BETWEEN STOCHASTIC ORDERINGS AND GENERALIZED STOCHASTIC PRECEDENCE [PDF]

open access: yesProbability in the Engineering and Informational Sciences, 2015
The concept of stochastic precedence between two real-valued random variables has often emerged in different applied frameworks. In this paper, we analyze several aspects of a more general, and completely natural, concept of stochastic precedence that also had appeared in the literature.
DE SANTIS, Emilio   +2 more
openaire   +3 more sources

On stochastic orders and total positivity

open access: yesESAIM: Probability and Statistics, 2023
The usual stochastic order and the likelihood ratio order between probability distributions on the real line are reviewed in full generality. In addition, for the distribution of a random pair (X, Y), it is shown that the conditional distributions of Y, given X = x, are increasing in x with respect to the likelihood ratio order if and only if the joint
Lutz Dümbgen, Alexandre Mösching
openaire   +3 more sources

Engineering Applications with Stress-Strength for a New Flexible Extension of Inverse Lomax Model: Bayesian and Non-Bayesian Inference

open access: yesAxioms, 2023
In this paper, we suggest a brand new extension of the inverse Lomax distribution for fitting engineering time data. The newly developed distribution, termed the transmuted Topp–Leone inverse Lomax (TTLILo) distribution, is characterized by an additional
Salem A. Alyami   +3 more
doaj   +1 more source

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