A homogeneously weighted moving average (HWMA) monitoring scheme is a recently proposed memory-type scheme that gained its popularity because of its simplicity and superiority over the exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) schemes in detecting small disturbances in the process. Most of the existing HWMA schemes are designed based on the assumption of normality. It is well-known that the performance of such monitoring schemes degrades significantly when this assumption is violated.
View Article and Find Full Text PDFThe homogeneously weighted moving average (HWMA) control chart is a new memory-type chart that allocates a specific weight to the current sample and the remaining weight is distributed equally to the previous samples. In this paper, the HWMA control chart is proposed for monitoring count data. This chart is based on the Conway-Maxwell (COM) distribution, which can be used to model under-spread and over-spread count data.
View Article and Find Full Text PDFIn these last few decades, control charts have received a growing interest because of the important role they play by improving the quality of the products and services in industrial and non-industrial environments. Most of the existing control charts are based on the assumption of certainty and accuracy. However, in real-life applications, such as weather forecasting and stock prices, operators are not always certain about the accuracy of an observed data.
View Article and Find Full Text PDFIn order to reduce the effect of autocorrelation on the monitoring scheme, a new sampling strategy is proposed to form rational subgroup samples of size . It requires sampling to be done such that: (i) observations from two consecutive samples are merged, and (ii) some consecutive observations are skipped before sampling. This technique which is a generalized version of the mixed samples strategy is shown to yield a better reduction of the negative effect of autocorrelation when monitoring the mean of processes with and without measurement errors.
View Article and Find Full Text PDFAge at first sexual intercourse may be a predictor of future sexual behaviour and an important indicator for exposure to HIV transmission. The purpose of the study is to establish risk factors associated with age at first intercourse among Lesotho women aged 15 to 49 years. The data used came from the 2009 Lesotho Demographic and Health Survey and probit models were applied for analysis.
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