qcs.pcr | R Documentation |
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.
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, ... )
object |
qcs object of type |
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 |
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. |
Montgomery, D.C. (1991) Introduction to Statistical Quality Control, 2nd
ed, New York, John Wiley & Sons.
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)
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