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A new CUSUM control chart under uncertainty with applications in petroleum and meteorology
This paper proposes a new cumulative sum (CUSUM) X chart under the assumption of uncertainty using the neutrosophic statistic (NS). The performance of the new chart is investigated in terms of the neutrosophic run length properties using the Monte Carlo simulations approach.
Collected Papers. Volume XIII
This thirteenth volume of Collected Papers is an eclectic tome of 88 papers in various fields of sciences, such as astronomy, biology, calculus, economics, education and administration, game theory, geometry, graph theory, information fusion, decision making, instantaneous physics, quantum physics, neutrosophic logic and set, non-Euclidean geometry, number theory, paradoxes, philosophy of science, scientific research methods, statistics, and others, structured in 17 chapters (Neutrosophic Theory and Applications; Neutrosophic Algebra; Fuzzy Soft Sets; Neutrosophic Sets; Hypersoft Sets; Neutrosophic Semigroups; Neutrosophic Graphs; Superhypergraphs; Plithogeny; Information Fusion; Statistics;...
Neutrosophic Computing and Machine Learning, Vol. 23
Neutrosophic Computing and Machine Learning (NCML) es una revista académica que ha sido creada para publicaciones de estudios avanzados en neutrosofía, conjunto neutrosófico, lógica neutrosófica, probabilidad neutrosófica, estadística neutrosófica, enfoques neutrosóficos para el aprendizaje automático, etc. y sus aplicaciones en cualquier campo. Some papers in this issue: Florentin Smarandache. Definición Mejorada de Lógica Neutrosófica No Estándar e Introducción a los Hiperreales Neutrosóficos (Quinta versión); Florentin Smarandache. La Estadística Neutrosófica es una extensión de la Estadística de Intervalos, mientras que la Estadística Plitogénica es la forma más g...
La Estadística Neutrosófica es una extensión de la Estadística de Intervalos, mientras que la Estadística Plitogénica es la forma más general de estadística. (Cuarta versión). Neutrosophic Statistics is an extension of Interval Statistics, while Plitogenic Statistics is the most general form of statistics (Fourth version)
In this paper we show that Neutrosophic Statistics is an extension of Interval Statistics, since it deals with all kinds of indeterminacy (with respect to data, inferential procedures, probability distributions, graphical representations, etc.), allows for indeterminacy reduction, and uses neutrosophic probability which is more general than imprecise and classical probabilities, and has more detailed corresponding probability density functions. Whereas Interval Statistics only deals with indeterminacy that can be represented by intervals. And we respond to the arguments of Woodall et al [1]. We show that not all indeterminacies (uncertainties) can be represented by intervals. Moreover, in some applications, we should use hesitant sets (which have less indeterminacy) instead of intervals. We redirect the authors to Plitogenic Probability and Plitogenic Statistics which are the most general forms of Multivariate Probability and Multivariate Statistics respectively (including, of course, Imprecise Probability and Interval Statistics as subclasses).
Nonparametric Statistical Process Control
A unique approach to understanding the foundations of statistical quality control with a focus on the latest developments in nonparametric control charting methodologies Statistical Process Control (SPC) methods have a long and successful history and have revolutionized many facets of industrial production around the world. This book addresses recent developments in statistical process control bringing the modern use of computers and simulations along with theory within the reach of both the researchers and practitioners. The emphasis is on the burgeoning field of nonparametric SPC (NSPC) and the many new methodologies developed by researchers worldwide that are revolutionizing SPC. Over the...
Multivariate Statistical Quality Control Using R
The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have led to an increased occurrence of industrial processes that utilize statistical process control and capability analysis. These analyses are performed almost exclusively with multivariate methodologies. The aim of this Brief is to present the most important MSQC techniques developed in R language. The book is divided into two parts. The first part contains the basic R elements, an introduction to statistical procedures, and the main aspects related to Statistical Quality Control (SQC). The second part covers the construction of multivariate control charts, the calculation of Multivariate Capability Indices.
Introduction to Statistical Process Control
A major tool for quality control and management, statistical process control (SPC) monitors sequential processes, such as production lines and Internet traffic, to ensure that they work stably and satisfactorily. Along with covering traditional methods, Introduction to Statistical Process Control describes many recent SPC methods that improve upon
Cumulative Sum Charts and Charting for Quality Improvement
Covering CUSUMs from an application-oriented viewpoint, while also providing the essential theoretical underpinning, this is an accessible guide for anyone with a basic statistical training. The text is aimed at quality practitioners, teachers and students of quality methodologies, and people interested in analysis of time-ordered data. Further support is available from a Web site containing CUSUM software and data sets.
Beyond Memory
South Africa possesses one of the richest popular music traditions in the world - from marabi to mbaqanga, from boeremusiek to bubblegum, from kwela to kwaito. Yet the risk that future generations of South Africans will not know their musical roots is very real. Of all the recordings made here since the 1930s, thousands have been lost for ever, for the powers-that-be never deemed them worthy of preservation. And if one peruses the books that exist on South African popular music, one still fi nds that their authors have on occasion jumped to conclusions that were not as foregone as they had assumed. Yet the fault lies not with them, rather in the fact that there has been precious little docum...
Distribution-Free Methods for Statistical Process Monitoring and Control
This book explores nonparametric statistical process control. It provides an up-to-date overview of nonparametric Shewhart-type univariate control charts, and reviews the recent literature on nonparametric charts, particularly multivariate schemes. Further, it discusses observations tied to the monitored population quantile, focusing on the Shewhart Sign chart. The book also addresses the issue of practically assuming the normality and the independence when a process is statistically monitored, and examines in detail change-point analysis-based distribution-free control charts designed for Phase I applications. Moreover, it introduces six distribution-free EWMA schemes for simultaneously monitoring the location and scale parameters of a univariate continuous process, and establishes two nonparametric Shewhart-type control charts based on order statistics with signaling runs-type rules. Lastly, the book proposes novel and effective method for early disease detection.
