qcs.pcr: Process capability indices for a given dataset and...

In qcr: Quality Control Review

Process capability indices for a given dataset and distribution

Description

Calculates the process capability indices cp, cpk, cpkL and cpkU for a given dataset and distribution. A histogramm with a density curve is displayed along with the specification limits and a Quantile-Quantile Plot for the specified distribution.

Usage

qcs.pcr(
  object,
  distribution = c("normal", "beta", "chi-squared", "exponential", "f", "geometric",
    "lognormal", "log-normal", "logistic", "t", "negative binomial", "poisson",
    "weibull", "gamma"),
  limits = c(lsl = -3, usl = 3),
  target = NULL,
  std.dev = NULL,
  boxcox = FALSE,
  lambda = c(-5, 5),
  confidence = 0.9973,
  plot = TRUE,
  main = NULL,
  ...
)

Arguments

object	qcs object of type "qcs.xbar" or "qcs.one".
distribution	character string that representing the probability distribution the data, such as:"normal","beta", "chi-squared", "exponential", "f", "geometric", "lognormal", "log-normal", "logistic","t", "negative binomial", "poisson", "weibull", "gamma".
limits	A vector specifying the lower and upper specification limits.
target	A value specifying the target of the process. If is NULL, the target is set at the middle value bewteen specification limits.
std.dev	A value specifying the within-group standard deviation.
boxcox	Logical value (default is FALSE). If TRUE, perform a Box-Cox transformation.
lambda	A vector specifying or numeric value indicating lambda for the transformation
confidence	A numeric value between 0 and 1 specifying the nivel for computing the specification limits.
plot	Logical value indicating whether graph should be plotted.
main	Title of the plot.
...	Arguments to be passed to or from methods.

References

Montgomery, D.C. (1991) Introduction to Statistical Quality Control, 2nd ed, New York, John Wiley & Sons.

Examples

library(qcr)
data(pistonrings) 
xbar <- qcs.xbar(pistonrings[1:125,],plot = TRUE)
limits = c(lsl = 73.99, usl = 74.01)
qcs.pcr(xbar, "normal", limits = limits) 
qcs.pcr(xbar, "weibull", limits = limits)

qcr documentation built on March 18, 2022, 6 p.m.