snPlot: snPlot: Signal-to-Noise-Ratio Plots

In r6qualitytools: R6-Based Statistical Methods for Quality Science

snPlot: Signal-to-Noise-Ratio Plots

Description

Creates a Signal-to-Noise Ratio plot for designs of type taguchiDesign.c with at least two replicates.

Usage

snPlot(object, type = "nominal", factors, fun = mean, response = NULL,
       points = FALSE, classic = FALSE, lty, xlab, ylab,
       main, ylim, l.col, p.col, ld.col, pch)

Arguments

object	An object of class taguchiDesign.c.
type	A character string specifying the type of the Signal-to-Noise Ratio plot. Possible values are: `nominal`: Nominal-the-best plot to equalize observed values to a nominal value. `smaller`: Smaller-the-better plot to minimize observed values. `larger`: Larger-the-better plot to maximize observed values. Default is `nominal`.
factors	The factors for which the effect plot is to be created.
fun	A function for constructing the effect plot such as mean, median, etc. Default is mean.
response	A character string specifying the response variable. If object contains multiple responses, this parameter selects one column to plot. Default is NULL.
points	A logical value. If TRUE, points are shown in addition to values derived from fun. Default is FALSE.
classic	A logical value. If TRUE, creates an effect plot as depicted in most textbooks. Default is FALSE.
lty	A numeric value specifying the line type to be used.
xlab	A title for the x-axis.
ylab	A title for the y-axis.
main	An overall title for the plot.
ylim	A numeric vector of length 2 specifying the limits of the y-axis.
l.col	A color for the lines.
p.col	A color for the points.
ld.col	A color for the dashed line.
pch	The symbol for plotting points.

Details

The Signal-to-Noise Ratio (SNR) is calculated based on the type specified:

• `nominal`:

  SN = 10 \cdot log(mean(y) / var(y))

• `smaller`:

  SN = -10 \cdot log((1 / n) \cdot sum(y^2))

• `larger`:

  SN = -10 \cdot log((1 / n) \cdot sum(1 / y^2))

Signal-to-Noise Ratio plots are used to estimate the effects of individual factors and to judge the variance and validity of results from an effect plot.

Value

An invisible data.frame containing all the single Signal-to-Noise Ratios.

Examples

tdo <- taguchiDesign("L9_3", replicates = 3)
tdo$.response(rnorm(27))
snPlot(tdo, points = TRUE, l.col = 2, p.col = 2, ld.col = 2, pch = 16, lty = 3)

r6qualitytools documentation built on Oct. 4, 2024, 1:09 a.m.