A univariate procedure for monitoring location and dispersion with ordered categorical data
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Pages (from-to) | 115-128 |
Journal / Publication | Communications in Statistics: Simulation and Computation |
Volume | 47 |
Issue number | 1 |
Online published | 2 Jun 2017 |
Publication status | Published - 2018 |
Link(s)
Abstract
The quality characteristic is usually measured by ordered attribute levels, such as good, general, and poor, which describe different magnitudes of the characteristic. The ordinal levels are determined by a continuous latent variable, the shifts of which are reflected by the observed counts in each level. This article devises a control procedure based on the discrepancy between observed average cumulative counts and their expected ones. Simulation results are shown to demonstrate its superior sensitivity in simultaneously detecting location and dispersion shifts of the latent variable. Flexibility in assigning the weight for each level can allow the chart to be more powerful.
Research Area(s)
- Categorical data, Dispersion, Location parameter, Statistical process control
Citation Format(s)
A univariate procedure for monitoring location and dispersion with ordered categorical data. / Wang, Junjie; Su, Qin; Xie, Min.
In: Communications in Statistics: Simulation and Computation, Vol. 47, No. 1, 2018, p. 115-128.
In: Communications in Statistics: Simulation and Computation, Vol. 47, No. 1, 2018, p. 115-128.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review