Chapter 3.11. A New Distribution-Free, Multivariate Discriminating Method

1989 ◽  
pp. 447-467
Author(s):  
B. Keller ◽  
H. Keller
Keyword(s):  
Distribution Free ◽  
New Distribution

scholarly journals Mixture Representations for the Joint Distribution of Lifetimes of two Coherent Systems with Shared Components

2013 ◽  
Vol 45 (4) ◽  
pp. 1011-1027 ◽  
Author(s):  
Jorge Navarro ◽  
Francisco J. Samaniego ◽  
N. Balakrishnan
Keyword(s):  
Representation Theorem ◽  
Joint Distribution ◽  
Survival Function ◽  
Coherent Systems ◽  
Comparative Performance ◽  
Component Failure ◽  
Distribution Free ◽  
Joint Survival Function ◽  
Signature Vector ◽  
New Distribution

The signature of a system is defined as the vector whose ith element is the probability that the system fails concurrently with the ith component failure. The signature vector is known to be a distribution-free measure and a representation of the system's survival function has been developed in terms of the system's signature. The present work is devoted to the study of the joint distribution of lifetimes of pairs of systems with shared components. Here, a new distribution-free measure, the ‘joint bivariate signature’, of a pair of systems with shared components is defined, and a new representation theorem for the joint survival function of the system lifetimes is established. The theorem is shown to facilitate the study of the dependence between systems and the comparative performance of two pairs of such systems.

Diagnosing Problems of Distribution-Free Multivariate Control Chart

2014 ◽  
Vol 971-973 ◽  
pp. 1602-1606
Author(s):  
Wen Li Shi ◽  
Xue Min Zi
Keyword(s):  
Control Chart ◽  
Historical Data ◽  
Important Application ◽  
Distribution Free ◽  
On Line ◽  
Multivariate Control Chart ◽  
Diagnostic Framework ◽  
Multivariate Control ◽  
Control Limits ◽  
New Distribution

In order to solve the problem of only have a few historical data that can be used in multivariate process monitoring, a new distribution-free multivariate control chart has been proposed. And in the control chart structure the control limits are determined on-line with the future observations and the historical data. Therefore, the proposed control chart has very important application in practice. However, the research doesn’t study the problem of the fault diagnosis after the control chart alarms. So we use LASSO-based diagnostic framework to identify when a detected shift has occurred and to isolate the shifted components.

scholarly journals Some New Distribution-Free Statistics

1965 ◽  
Vol 36 (1) ◽  
pp. 203-214 ◽  
Author(s):  
C. B. Bell ◽  
K. A. Doksum
Keyword(s):  
Distribution Free ◽  
New Distribution

scholarly journals Finding Cliques in Social Networks: A New Distribution-Free Model

2020 ◽  
Vol 49 (2) ◽  
pp. 448-464
Author(s):  
Jacob Fox ◽  
Tim Roughgarden ◽  
C. Seshadhri ◽  
Fan Wei ◽  
Nicole Wein
Keyword(s):  
Social Networks ◽  
Distribution Free ◽  
Free Model ◽  
New Distribution

A New Distribution-Free Control Chart for Monitoring Process Median Based on the Statistic of the Sign Test

2021 ◽  
Vol 50 (1) ◽  
pp. 20210135
Author(s):  
Saber Ali ◽  
Zameer Abbas ◽  
Hafiz Zafar Nazir ◽  
Muhammad Riaz ◽  
Muhammad Abid
Keyword(s):  
Control Chart ◽  
Sign Test ◽  
Distribution Free ◽  
Monitoring Process ◽  
New Distribution

scholarly journals Mixture Representations for the Joint Distribution of Lifetimes of two Coherent Systems with Shared Components

2013 ◽  
Vol 45 (04) ◽  
pp. 1011-1027 ◽  
Author(s):  
Jorge Navarro ◽  
Francisco J. Samaniego ◽  
N. Balakrishnan
Keyword(s):  
Representation Theorem ◽  
Joint Distribution ◽  
Survival Function ◽  
Coherent Systems ◽  
Comparative Performance ◽  
Component Failure ◽  
Distribution Free ◽  
Joint Survival Function ◽  
Signature Vector ◽  
New Distribution

The signature of a system is defined as the vector whoseith element is the probability that the system fails concurrently with theith component failure. The signature vector is known to be a distribution-free measure and a representation of the system's survival function has been developed in terms of the system's signature. The present work is devoted to the study of the joint distribution of lifetimes of pairs of systems with shared components. Here, a new distribution-free measure, the ‘joint bivariate signature’, of a pair of systems with shared components is defined, and a new representation theorem for the joint survival function of the system lifetimes is established. The theorem is shown to facilitate the study of the dependence between systems and the comparative performance of two pairs of such systems.

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