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Fellag, Hocine; Ibazizen, Mohamed

doi:10.1023/a:1011318515549

Cited by 6 publications

(1 citation statement)

References 5 publications

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“…Noise usually follows white noise; however, exponential white noise can also be followed by noise. As Fellag & Ibazizen [9] have done, a specific example of white noise with an exponential distribution will be considered.…”

Section: Introductionmentioning

confidence: 99%

The Development and Evaluation of Homogenously Weighted Moving Average Control Chart based on an Autoregressive Process

Sunthornwat,

Sukparungsee,

Areepong

2024

HighTech. Innov. J.

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This research aims to investigate a Homogenously Weighted Moving Average (HWMA) control chart for detecting minor and moderate shifts in the process mean. A mathematical model for the explicit formulae of the average run length (ARL) of the HWMA control chart based on the autoregressive (AR) process is presented. The efficacy of the HWMA control chart is evaluated based on the average run length, the standard deviation of run length (SDRL), and the median run length (MRL). As illustrations of the design and implementation of the HWMA control chart, numerical examples are provided. In numerous instances, a comparative analysis of the HWMA control chart relative to the Extended Exponentially Weighted Moving Average (Extended EWMA) and cumulative sum (CUSUM) control charts with mean process shifts is performed in detail. Additionally, the relative mean index (RMI), the average extra quadratic loss (AEQL), and the performance comparison index (PCI) are utilized to evaluate the performance of control charts. For various shift sizes, the HWMA control chart is superior to the Extended EWMA and CUSUM control charts. This study applies empirical data from the area of economics to validate the explicit formula of ARL values for the HWMA control chart. Doi: 10.28991/HIJ-2024-05-01-02 Full Text: PDF

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Section: Introductionmentioning

confidence: 99%