Statistics for Spatial Data.

Economic Control of Quality of Manufactured Product.

In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the construction of multivariate control charts, based on multivariate statistical techniques such as principal components analysis (PCA) and partial lest squares (PLS). Finally, we describe the most significant methods for the interpretation of an out-of-control signal.

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Multivariate statistical process control charts: an overview

Statistical methods in medical research , Statistical methods in medical research , کتابخانه دیجیتال جندی شاپور اهواز

Statistical methods in medical research

Multivariate Statistical Process Control Charts: An Overview

The aim of this paper is to present the basic principles and recent advances in the area of statistical process control charting with the aid of runs rules. More specifically, we review the well known Shewhart type control charts supplemented with additional rules based on the theory of runs and scans. The motivation for this article stems from the fact that during the last decades, the performance improvement of the Shewhart charts by exploiting runs rules has attracted continuous research interest. Furthermore, we briefly discuss the Markov chain approach which is the most popular technique for studying the run length distribution of run based control charts.

Statistical Process Control using Shewhart Control Charts with Supplementary Runs Rules

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1028242_code383271.pdf?abstractid=1028242&mirid=4

Objectives: The incidence and antimicrobial susceptibilities of Ureaplasma urealyticum and Mycoplasma hominis, isolated from vaginal and endocervical swabs collected from 369 outpatient women, were determined. Methods: Isolation, identification and typing of the pathogens were performed by means of conventional methods. The antimicrobial susceptibilities of the genital mycoplasmas were determined with commercially available kits and evaluated according to the CLSI. Results and conclusions: In 65 (47.44%) out of the 137 positive specimens, U. urealyticum was grown as a single pathogen, in 0.72% M. hominis was grown as a single pathogen and in 2.92% both urogenital mycoplasmas were grown. In the remaining specimens (48.90%), there was a mixed growth with other microbes. Of the isolated U. urealyticum strains, 87.4% and 98.2% were susceptible to tetracycline and doxycycline, respectively, 79.2% were susceptible to josamycin, 48.6% were susceptible to clarithromycin and 91.8% were susceptible to pristinamycin, while erythromycin, azithromycin, ciprofloxacin and ofloxacin proved to be inactive against most of the strains. M. hominis isolates were 100% susceptible to tetracycline, doxycycline and pristinamycin, while susceptibilities to the other antimicrobial agents varied mainly in the range of ‘intermediate’ or ‘resistant’. As results originating from similar studies from various countries are very controversial, the simplest way to avoid therapeutic failures would be the implementation of rational treatment regimens based on culture isolation and the in vitro determination of the antimicrobial susceptibility of genital mycoplasmas in each clinical case.

Sotiris Bersimis

Papers

Multivariate statistical process control charts: an overview

Multivariate Statistical Process Control Charts: An Overview

Statistical Process Control using Shewhart Control Charts with Supplementary Runs Rules

Multivariate Statistical Process Control Charts: An Overview

Incidence and antimicrobial susceptibilities of genital mycoplasmas in outpatient women with clinical vaginitis in Athens, Greece.