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An adaptive thresholding-based process variability monitoring
(
Taylor and Francis Inc.
, 2019 , Article)
In high-dimensional processes, monitoring process variability is considerably difficult due to the large number of variables and the limited number of samples. Monitoring changes in the covariance matrix of a multivariate ...
Penalized Conway-Maxwell-Poisson regression for modelling dispersed discrete data: The case study of motor vehicle crash frequency
(
Elsevier B.V.
, 2019 , Article)
Statistical modelling of road crashes has been of extreme interest to researchers over the last decades. Such models are necessary for the investigation of the opportunities for road safety improvement. The motor vehicle ...
Control charts for variability monitoring in high-dimensional processes
(
Elsevier Ltd
, 2019 , Article)
Monitoring process variability is associated with detecting changes in the covariance matrix of a multivariate normal process. Most monitoring methods estimate the sample covariance matrix and compare it with the in-control ...