Jean-Claude Malela-Majika

Bio: Jean-Claude Malela-Majika is an academic researcher from University of South Africa. The author has contributed to research in topics: Control chart & Moving average. The author has an hindex of 10, co-authored 47 publications receiving 293 citations. Previous affiliations of Jean-Claude Malela-Majika include University of Pretoria & Tshwane University of Technology.

Double exponentially weighted moving average control chart with supplementary runs-rules

Abstract: Enhancing the sensitivity of control charts for detecting small process shift is desirable and may be done in different ways. In this paper, we propose the double exponentially weighted moving aver...

Distribution-free precedence control charts with improved runs-rules

Abstract: Distribution-free nonparametric control charts are helpful in applications where we do not have enough information about the underlying distribution. The Shewhart precedence charts is a class of Phase I nonparametric charts for location. One of these charts, called the median precedence chart Med chart hereafter, uses the median of the test sample as the charting statistic, whereas another chart, called the minimum precedence chart Min chart hereafter, uses the minimum. In this paper, we first study the comparative performance of the Min and the Med charts, respectively, in terms of their in-control and out-of-control run-length properties in an extensive simulation study. It is seen that neither chart is best as each has its strength in certain situations. Next, we consider enhancing their performance by adding some supplementary runs-rules. It is seen that the new charts present very attractive run-length properties, that is, they outperform their competitors in many situations. A summary and some concluding remarks are given. Copyright © 2016 John Wiley & Sons, Ltd.

Distribution-free Phase II Mann–Whitney control charts with runs-rules

Abstract: The research of the third author was partly supported by a National Research Foundation grant (Reference: TTK14061168807,UID: 94102).

New distribution-free memory-type control charts based on the Wilcoxon rank-sum statistic

Abstract: In this paper, a new distribution-free double exponentially weighted moving average (DEWMA) control chart based on the Wilcoxon rank-sum (WRS) test without any distributional assumption of the unde...

Generally weighted moving average monitoring schemes: Overview and perspectives

Abstract: An overview of monitoring schemes from a class called generally weighted moving average (GWMA) is provided. A GWMA scheme is an extended version of the exponentially weighted moving average (EWMA) scheme with an additional adjustment parameter that introduces more flexibility in the GWMA model as it adjusts the kurtosis of the weighting function so that the GWMA scheme can be designed such that it has an advantage over the corresponding EWMA scheme in the detection of certain shift values efficiently. The parametric and distribution-free GWMA schemes to monitor various quality characteristics and its existing enhanced versions (i.e. double GWMA, composite Shewhart-GWMA, mixed GWMA-CUSUM and mixed CUSUM-GWMA) have better performance than their corresponding EWMA counterparts in many situations; hence, all such existing research works discussing GWMA-related schemes (i.e. 61 publications in total) are documented and categorized in such a manner that it is easy to identify research gaps. Finally, a number of possible future research ideas are provided.

Runs and Scans With Applications

Abstract: of the conditional distribution speciŽ cations. Chapters 8 and 10 extend these methods from two to more dimensions. Chapter 9 investigates estimation in conditionally speciŽ ed models. Chapter 11 considers models speciŽ ed by conditioning on events speciŽ ed by one variable exceeding a value rather than equaling a value, and Chapter 12 considers models for extreme-value data. Chapter 13 extends conditional speciŽ cation to Bayesian analysis. Chapter 14 describes the related simultaneous-equation models, and Chapter 15 ties in some additional topics. An appendix describes methods of simulation from conditionally speciŽ ed models. Chapters 1–4, plus Chapters 9 and 13, comprise a lively overview of conditionally speciŽ ed models. The remainder of the text constitutes a detailed catalog of results speciŽ c to different conditional distributions. Although this catalog is certainly of value, the reader desiring a briefer and less detailed introduction to the subject might skip the remainder at Ž rst reading. This text is a revision of the book by Arnold, Costillo, and Sarabia (1992). The current version is of similar breadth, but with much more depth than the original. The text is clearly written and accessible with relatively few mathematical prerequisites. I found surprisingly few typographical errors; the authors are to be congratulated for this. In a few cases, regularity conditions for results are not given in full. Generally, this causes little confusion, although something does appear to be missing in the statement of Aczél’s key theorem (Theorem 1.3). Fortunately, most of the results in the sequel are derived from corollaries to this theorem, and the corollaries are stated more precisely. I noted few gaps in the material covered. The only area that I thought was insufŽ ciently represented was application to Markov chain Monte Carlo. Conditional speciŽ cation is particularly important in Gibbs sampling. I believe that many practitioners would beneŽ t from a discussion of the issues involved in these sampling schemes. Each chapter contains numerous exercises. These exercises appear to be at an appropriate level for a graduate course in statistics, and appear to provide appropriate reinforcement for the material in the preceding chapters.

What a performance

Abstract: The recent appearance of the annual reports of most publicly quoted petroleum companies for the financial year 2003, together with Shell having to substantially downgrade its proven reserves, makes it a timely moment to consider 2003 performance for a range of petroleum companies, writes David Wood.