bcc: Beta Control Charts

View source: R/bcc.R

bccR Documentation

Beta Control Charts


Creates and displays a Beta control chart using the specified data, sample sizes, and type. This is the main function for generating control charts in this package.


bcc(data, sizes = NULL, type, title = NULL)



A numeric vector of data values to be plotted on the control chart.


An optional numeric vector of sample sizes. This parameter is required for type 1 charts, which are designed for discrete data.


An integer representing the type of control chart. There are two possible types: 1 for discrete data (such as proportions or counts) and 2 for continuous data.


An optional string specifying the title of the plot.


The Beta Chart presents control limits based on the Beta probability distribution. It is used for monitoring fraction data from a Binomial distribution as a replacement for p-Charts. The Beta Chart has been applied in three real studies, demonstrating its effectiveness. Comparative analysis revealed that: (i) the Beta approximation to the Binomial distribution is more appropriate for values confined within the [0, 1] interval; and (ii) the proposed charts are more sensitive to the average run length (ARL) in both in-control and out-of-control process monitoring. Overall, the Beta Charts outperform the Shewhart control charts for monitoring fraction data.


A plot of the Beta control chart.


# Example for type 1 chart with discrete data
data <- c(0.12, 0.18, 0.14, 0.28, 0.22)
sizes <- c(101, 98, 110, 105, 95)
bcc(data, sizes, type=1, title="Beta Control Chart for Discrete Data")

# Example for type 2 chart with continuous data
data <- c(0.59, 0.67, 0.61, 0.70, 0.59)
bcc(data, type=2, title="Beta Control Chart for Continuous Data")

# Example changing the title of the chart
data <- c(0.07, 0.13, 0.21, 0.25, 0.19)
sizes <- c(52, 49, 51, 53, 48)
bcc(data, sizes, type=1, title="Custom Title: Beta Control Chart for Discrete Data")

bcc documentation built on June 22, 2024, 7:25 p.m.

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