simProc

noise

This is a function to simulate a black box process for teaching the use of designed experiments. The optimal factor settings can be found using a sequential assembly strategy i.e. apply a 2^k factorial design first, calculate the path of the steepest ascent, again apply a 2^k factorial design and augment a star portion to find the optimal factor settings. Of course other strategies are possible.

design

This is a package for teaching statistical methods in the
        field of Quality Science. It covers distribution fitting,
        process capability, Gage R&R, factorial, fractional factorial
        design as well as response surface methods including the use of
        desirability functions. Define - Pareto Chart; Measure -
        Probability and Quantile-Quantile Plots, Process Capability
        Ratios for various distributions and Gage RR Analyze i.e.
        Pareto Chart, Multi-Vari Chart, Dot Plot; Improve - Full and
        fractional factorial, response surface and mixture designs as
        well as the desirability approach for simultaneous optimization
        of more than one response variable. Normal, Pareto and Lenth
        Plot of effects as well as Interaction Plots; Control - Quality
        Control Charts can be found in the qcc package. The focus is on
        teaching the statistical methodology used in the Quality
        Sciences.

simProc: Simulated Process

Description

Usage

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Details

See Also

Examples