MRControlLimits - Maple Help

ProcessControl

 MRControlLimits
 compute control limits for the MR chart

 Calling Sequence MRControlLimits(X, options)

Parameters

 X - data options - (optional) equation(s) of the form option=value where option is one of confidencelevel, ignore, or rbar; specify options for computing the control limits

Description

 • The MRControlLimits command computes the upper and lower control limits for the MR chart. Unless explicitly given, the average of the moving ranges of two observations of the underlying quality characteristic is computed based on the data.
 • The first parameter X is a single data sample, given as a Vector or list. Each value represents an individual observation.

Computation

 • All computations involving data are performed in floating-point; therefore, all data provided must have type realcons and all returned solutions are floating-point, even if the problem is specified with exact values.

Options

 The options argument can contain one or more of the following options.
 • confidencelevel=realcons -- This option specifies the required confidence level. The default value is 0.9973, corresponding to a 3 sigma confidence level.
 • ignore=truefalse -- This option controls how missing values are handled by the MRControlLimits command. Missing values are represented by undefined or Float(undefined). So, if ignore=false and X contains missing data, the MRControlLimits command returns undefined. If ignore=true, all missing items in X are ignored. The default value is true.
 • rbar=deduce or realcons -- This option specifies the average of the moving ranges of two observations.

Examples

 > $\mathrm{with}\left(\mathrm{ProcessControl}\right):$
 > $\mathrm{infolevel}\left[\mathrm{ProcessControl}\right]≔1:$
 > $A≔\left[33.75,33.05,34.00,33.81,33.46,34.02,33.68,33.27,33.49,33.20,33.62,33.00,33.54,33.12,33.84\right]:$
 > $\mathrm{MRControlLimits}\left(A\right)$
 $\left[{0.}{,}{1.57127089652357}\right]$ (1)
 > $l≔\mathrm{MRControlLimits}\left(A,\mathrm{confidencelevel}=0.95\right)$
 ${l}{≔}\left[{0.}{,}{1.57127089652357}\right]$ (2)

References

 Montgomery, Douglas C. Introduction to Statistical Quality Control. 2nd ed. New York: John Wiley & Sons, 1991.