tolerance (version 3.0.0)

plottol: Plotting Capabilities for Tolerance Intervals

Description

Provides control charts and/or histograms for tolerance bounds on continuous data as well as tolerance ellipses for data distributed according to bivariate and trivariate normal distributions. Scatterplots with regression tolerance bounds and interval plots for ANOVA tolerance intervals may also be produced.

Usage

plottol(tol.out, x, y = NULL, y.hat = NULL, 
        side = c("two", "upper", "lower"), 
        plot.type = c("control", "hist", "both"), 
        x.lab = NULL, y.lab = NULL, z.lab = NULL, ...)

Value

plottol can return a control chart, histogram, or both for continuous data along with the calculated tolerance intervals. For regression data, plottol returns a scatterplot along with the regression tolerance bounds. For ANOVA output, plottol

returns an interval plot for each factor.

Arguments

tol.out

Output from any continuous (including ANOVA) tolerance interval procedure or from a regression tolerance bound procedure.

x

Either data from a continuous distribution or the predictors for a regression model. If this is a design matrix for a linear regression model, then it must be in matrix form AND include a column of 1's if there is to be an intercept. Note that multiple predictors are only allowed if considering polynomial regression. If the output for tol.out concerns ANOVA tolerance intervals, then x must be a data frame.

y

The response vector for a regression setting. Leave as NULL if not doing regression tolerance bounds.

y.hat

The fitted values from a nonparametric smoothing routine if plotting nonparametric regression tolerance bounds. Otherwise, leave as NULL.

side

side = "two" produces plots for either the two-sided tolerance intervals or both one-sided tolerance intervals. This will be determined by the output in tol.out. side = "upper" produces plots showing the upper tolerance bounds. side = "lower" produces plots showing the lower tolerance bounds.

plot.type

plot.type = "control" produces a control chart of the data along with the tolerance bounds specified by side. plot.type = "hist" produces a histogram of the data along with the tolerance bounds specified by side. plot.type = "both" produces both the control chart and histogram. This argument is ignored when plotting regression data.

x.lab

Specify the label for the x-axis.

y.lab

Specify the label for the y-axis.

z.lab

Specify the label for the z-axis.

...

Additional arguments passed to the plotting function used for the control charts or regression scatterplots.

References

Montgomery, D. C. (2005), Introduction to Statistical Quality Control, Fifth Edition, John Wiley & Sons, Inc.

Examples

## 90%/90% 1-sided Weibull tolerance intervals for a sample
## of size 150. 

set.seed(100)
x <- rweibull(150, 3, 75)
out <- exttol.int(x = x, alpha = 0.15, P = 0.90, 
                  dist = "Weibull")
out

plottol(out, x, plot.type = "both", side = "lower", 
        x.lab = "Weibull Data")

## 90%/90% trivariate normal tolerance region. 

set.seed(100)
x1 <- rnorm(100, 0, 0.2)
x2 <- rnorm(100, 0, 0.5)
x3 <- rnorm(100, 5, 1)
x <- cbind(x1, x2, x3)
mvtol.region(x = x, alpha = c(0.10, 0.05, 0.01), 
             P = c(0.90, 0.95, 0.99), B = 1000) 

out2 <- mvtol.region(x = x, alpha = 0.10, P = 0.90, B = 1000) 
out2
plottol(out2, x)

## 95%/95% 2-sided linear regression tolerance bounds
## for a sample of size 100. 

set.seed(100)
x <- runif(100, 0, 10)
y <- 20 + 5*x + rnorm(100, 0, 3)
out3 <- regtol.int(reg = lm(y ~ x), new.x = data.frame(x = c(3, 6, 9)), 
                   side = 2, alpha = 0.05, P = 0.95)
plottol(out3, x = cbind(1, x), y = y, side = "two", x.lab = "X", 
        y.lab = "Y")