The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

Rspc

Overview

Rspc is an implementation of nelson rules for control charts in R. The RSPC package implements some Statistical Process Control methods, namely Levey-Jennings type of I (individuals) chart, Shewhart C (count) chart and Nelson rules. Typical workflow is taking the time series, specify the control limits, and list of Nelson rules you want to evaluate. There are several options how to modify the rules (one sided limits, numerical parameters of rules, etc.). Package is also capable of calculating the control limits from the data (so far only for i-chart and c-chart are implemented).

Installation

# The easiest way to get Rspc is to install it from CRAN repository:
install.packages("Rspc")

# Or the development version from GitHub:
# install.packages("devtools")
devtools::install_github("Merck/SPC_Package")

Usage

#load the package
library(Rspc)
# generate some data
data <- rnorm(10) 
# evaluate all the Nelson rules, 
# calculate control limits from data (lcl, cl, ucl are not provided) using formulas for i-chart, 
# don't modify any rule parameters (parRules = NULL)
EvaluateRules(x = data, type = 'i', whichRules = 1:8, lcl = NA, cl = NA, ucl = NA)
#The vector 'x' is the only compulsory parameter, default values for the rest is as above. 
#The code above is equivalent to data = rnorm(100); EvaluateRules(x = data).

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.