bcc: Beta Control Charts
In bcc: Beta Control Charts
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Beta Control Charts
Description
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.
Usage
bcc(data, sizes = NULL, type, title = NULL)
Arguments
data
A numeric vector of data values to be plotted on the control chart.
sizes
An optional numeric vector of sample sizes. This parameter is required for type 1 charts, which are designed for discrete data.
type
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.
title
An optional string specifying the title of the plot.
Details
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.
Value
A plot of the Beta control chart.
Examples
# 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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| bcc | R Documentation |
Beta Control Charts
Description
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.
Usage
bcc(data, sizes = NULL, type, title = NULL)
Arguments
data |
A numeric vector of data values to be plotted on the control chart. |
sizes |
An optional numeric vector of sample sizes. This parameter is required for type 1 charts, which are designed for discrete data. |
type |
An integer representing the type of control chart. There are two possible types: |
title |
An optional string specifying the title of the plot. |
Details
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.
Value
A plot of the Beta control chart.
Examples
# 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")
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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