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MSQC (version 1.0.2)

Multivariate Statistical Quality Control

Description

This is a toolkit for multivariate process monitoring. It computes several multivariate control charts e.g. Hotelling, Chi-squared, MEWMA, MCUSUM and Generalized Variance. Ten didactic datasets are included. It includes some techniques for assessing multivariate normality e.g. Mardia's, Royston's and Henze-Zirkler's tests. Please, see the NEWS file for the latest changes in the package.

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Version

Install

install.packages('MSQC')

Monthly Downloads

63

Version

1.0.2

License

GPL-2 | GPL-3

Maintainer

Edgar SantosFernandez

Last Published

June 1st, 2016

Functions in MSQC (1.0.2)

Bimetal dataset during the Phase I

Target archery dataset during the elimination stage (used as Phase II)

Dowel pin dataset for the Phase II

Sample covariance

Dowel pin dataset for the Phase I

Bimetal dataset during the Phase II

Target archery dataset during the ranking round (used as Phase I)

D'Agostino test

Carbon fiber tubing during the Phase I

Carbon fiber tubing during the Phase II

Henze-Zirkler test

Largest ellipsoid

confidence ellipsoid

Coordinates of the pitches called "strike" by umpire Ron Kulpa

Industrial dataset collected in Phase II

Generalized Variance Control Chart

Industrial dataset collected during the Phase I

Dataset of a glass manufacturing process during the Phase I

Dataset of a glass manufacturing process during the Phase II

Multivariate Control Chart

Right skewed dataset

A mechanical process (Phase I)

Draws a rectangular prism

A mechanical process (Phase II)

A pitching log of C.C. Sabathia on July 10, 2011.

Multivariate Statistical Quality Control

Individual observations from the MLB pitcher C.C. Sabathia from the game on July 10, 2011.

A water quality test (Phase II)

A water quality test (Phase I)

A pitching log of C.C. Sabathia on August 12, 2011