Browsing by UP Author "Human, Schalk William"

Browsing by UP Author "Human, Schalk William"

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  • Capturing a change in the covariance structure of a multivariate process 
    Bekker, Andriette, 1958-; Ferreira, Johannes Theodorus; Human, Schalk William; Adamski, Karien (MDPI, 2022-01-13)
    This research is inspired from monitoring the process covariance structure of q attributes where samples are independent, having been collected from a multivariate normal distribution with known mean vector and unknown ...
  • A double generally weighted moving average exceedance control chart 
    Masoumi Karakani, Hossein; Human, Schalk William; Van Niekerk, Janet (Wiley, 2019-02)
    Since the inception of control charts by W. A. Shewhart in the 1920s, they have been increasingly applied in various fields. The recent literature witnessed the development of a number of nonparametric (distribution‐free) ...
  • Generalized multivariate beta distribution : control charting when the measurements are from an exponential distribution 
    Adamski, Karien; Human, Schalk William; Bekker, Andriette, 1958- (Springer, 2012)
    In Statistical Process Control (SPC) there exists a need to model the runlength distribution of a Q-chart that monitors the process mean when measurements are from an exponential distribution with an unknown parameter. ...
  • A generally weighted moving average chart for time between events 
    Chakraborty, Niladri; Human, Schalk William; Balakrishnan, N. (Taylor and Francis, 2017-05)
    Shewhart-type attribute charts are known to be inefficient for small changes in monitoring nonconformities. An alternative way is to use a time-weighted chart to monitor the time between events (TBE). We propose a one-sided ...
  • A generally weighted moving average exceedance chart 
    Chakraborty, Niladri; Human, Schalk William; Balakrishnan, Narayanaswamy (Taylor and Francis, 2018-03)
    Distribution-free control charts gained momentum in recent years as they are more efficient in detecting a shift when there is a lack of information regarding the underlying process distribution. However, a distribution-free ...
  • A generally weighted moving average signed-rank control chart 
    Chakraborty, Niladri; Chakraborti, Subhabrata; Human, Schalk William; Balakrishnan, N. (Wiley, 2016-12)
    The idea of process monitoring emerged so as to preserve and improve the quality of a manufacturing process. In this regard, control charts are widely accepted tools in the manufacturing sector for monitoring the quality ...
  • Improved Shewhart-type runs-rules nonparametric sign charts 
    Kritzinger, Pierre; Human, Schalk William; Chakraborti, Subhabrata (Taylor & Francis, 2014-07)
    Runs-rules are typically incorporated in control charts to increase their sensitivity to detect small process shifts. However, a drawback of this approach is that runs-rules charts are unable to detect large shifts quickly. ...
  • Noncentral generalized multivariate Beta Type II distribution 
    Adamski, Karien; Human, Schalk William; Bekker, Andriette, 1958-; Roux, Jacobus J.J. (National Statistical Institute of Portugal, 2013-03)
    The distribution of the variables that originates from monitoring the variance when the mean encountered a sustained shift is considered — specifically for the case when measurements from each sample are independent and ...
  • Nonparametric EWMA sign chart for location based on individual measurements 
    Graham, Marien Alet; Chakraborti, Subhabrata; Human, Schalk William (Routledge, 2011-06)
    Nonparametric control charts are useful when there is limited or complete lack of knowledge about the form of the underlying distribution. Though traditional statistical process control (SPC) applications of control ...
  • A nonparametric exponentially weighted moving average signed-rank chart for monitoring location 
    Graham, Marien Alet; Chakraborti, Subhabrata; Human, Schalk William (Elsevier, 2011-08)
    Nonparametric control charts can provide a robust alternative in practice to the data analyst when there is a lack of knowledge about the underlying distribution. A nonparametric exponentially weighted moving average (NPEWMA) ...
  • Nuwe ontwikkeling tot die bivariate betaveld 
    Jacobs, Rianne; Bekker, Andriette, 1958-; Human, Schalk William (Suid Afrikaanse Akademie vir Wetenskap & Kuns, 2011)
    In this paper, the bivariate Kummer-beta type IV distribution, which extends the Jones’ bivariate beta distribution, is discussed. The probability density functions of the product and ratio of the components of this ...
  • On the bivariate Kummer-beta type IV distribution 
    Jacobs, Rianne; Bekker, Andriette, 1958-; Human, Schalk William (Routledge, 2012)
    In this paper the non-central bivariate Kummer-beta type IV distribution is introduced and derived via the Laplace transform of the non-central bivariate beta distribution by Gupta et al. (2009). We focus on and discuss ...
  • A phase II nonparametric control chart based on precedence statistics with runs-type signaling rules 
    Chakraborti, Subhabrata; Eryilmaz, S.; Human, Schalk William (Elsevier, 2008-09)
    Nonparametric control charts do not require knowledge about the shape of the underlying distribution and can thus be attractive in certain situations. Two new Shewhart- type nonparametric control charts are proposed for ...
  • Properties and performance of the c-chart for attributes data 
    Chakraborti, Subhabrata; Human, Schalk William (Taylor & Francis, 2008)
    The effects of parameter estimation are examined for the well-known c-chart for attributes data. The exact run length distribution is obtained for Phase II applications, when the true average number of non-conformities, ...
  • Robustness of the EWMA control chart for individual observations 
    Human, Schalk William; Kritzinger, Pierre; Chakraborti, Subhabrata (Taylor & Francis, 2011-10)
    The traditional exponentially weighted moving average (EWMA) chart is one of the most popular control charts used in practice today. The in-control robustness is the key to the proper design and implementation of any ...