Simulation-Based Comparative Analysis of Nonparametric Control Charts with Runs-Type Rules

Mapping Intimacies ◽

10.5772/intechopen.91040 ◽

2020 ◽

Cited By ~ 1

Author(s):

Ioannis S. Triantafyllou

Keyword(s):

Comparative Analysis ◽

Order Statistics ◽

Control Charts ◽

Control Performance ◽

Distribution Free ◽

Underlying Process ◽

Simulation Based

In this chapter, we study well-known distribution-free Shewhart-type monitoring schemes based on order statistics. In order to empower the in- and out-of-control performance of the control charts being under consideration, several runs-type rules are enhanced. The simulation-based experimentation carried out reveals that the proposed schemes achieve remarkable efficiency for detecting possible shifts in the distribution of the underlying process.

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Distribution-Free Phase II Control Charts Based on Order Statistics with Runs-Rules

Distribution-Free Methods for Statistical Process Monitoring and Control ◽

10.1007/978-3-030-25081-2_7 ◽

2020 ◽

pp. 219-241

Author(s):

Ioannis S. Triantafyllou ◽

Nikolaos I. Panayiotou

Keyword(s):

Order Statistics ◽

Phase Ii ◽

Control Charts ◽

Distribution Free ◽

Runs Rules ◽

Phase Ii Control Charts

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On dynamic mutual information for bivariate lifetimes

Advances in Applied Probability ◽

10.1239/aap/1449859804 ◽

2015 ◽

Vol 47 (4) ◽

pp. 1157-1174 ◽

Cited By ~ 13

Author(s):

Jafar Ahmadi ◽

Antonio Di Crescenzo ◽

Maria Longobardi

Keyword(s):

Mutual Information ◽

Order Statistics ◽

Random Sample ◽

Exponential Model ◽

Multicomponent Systems ◽

Distribution Free ◽

Lifetime Distributions ◽

Different Ages ◽

Special Case ◽

Residual Lifetimes

We consider dynamic versions of the mutual information of lifetime distributions, with a focus on past lifetimes, residual lifetimes, and mixed lifetimes evaluated at different instants. This allows us to study multicomponent systems, by measuring the dependence in conditional lifetimes of two components having possibly different ages. We provide some bounds, and investigate the mutual information of residual lifetimes within the time-transformed exponential model (under both the assumptions of unbounded and truncated lifetimes). Moreover, with reference to the order statistics of a random sample, we evaluate explicitly the mutual information between the minimum and the maximum, conditional on inspection at different times, and show that it is distribution-free in a special case. Finally, we develop a copula-based approach aiming to express the dynamic mutual information for past and residual bivariate lifetimes in an alternative way.

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