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Confidence Interval Plot

version 1.0 (169 KB) by Jennie Chung
Creates a chart with a mean line within a shaded confidence interval area.

43 Downloads

Updated 08 Sep 2021

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Confidence Interval Plot

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Version: 1.0

This chart creates a mean line within a shaded confidence interval area.

Example confidenceIntervalPlot

Syntax

  • confidenceIntervalPlot(x,y) create a line which passes through the means of the y-values for each unique x-value. Plot this line within a shaded area covering a 95% confidence interval for each unique x-value. x and y must be numeric vectors of equal length.
  • confidenceIntervalPlot(x,y,alpha) create a line which passes through the means of the y-values for each unique x-value. Plot this line within a shaded area covering a 100 * (1 - alpha)% confidence interval for each unique x-value. x and y must be numeric vectors of equal length.
  • confidenceIntervalPlot() create an empty confidence interval plot.
  • confidenceIntervalPlot(___,Name,Value) specifies additional options for the confidence interval plot using one or more name-value pair arguments. Specify the options after all other input arguments.
  • confidenceIntervalPlot(parent,___) creates the confidence interval plot in the specified parent.
  • h = confidenceIntervalPlot(___) returns the confidenceIntervalPlot object. Use h to modify properties of the plot after creating it.

Name-Value Pair Arguments/Properties

  • XData (1 x n numeric vector) x-values of the raw data.
  • YData (1 x n numeric vector) y-values of the raw data.
  • CenterXData (1 x n numeric vector) read-only property. x-values used to plot the center line. Unless the name/value pair 'edges' is used, contains unique x-values in XData.
  • CenterYData (1 x n numeric vector) y-values used to plot the center line. Unless the name/value pair 'edges' is used or CenterYData is manually specified by the user, contains the mean of y-values for each unique x-value in XData.
  • CenterYDataMode ('auto' or 'manual') mode describing the method by which the center line is determined. In 'auto' mode, the mean of the y-values for each center line x-value used. In 'manual' mode, the user can specify CenterYData as Name/Value pair.
  • Alpha (scalar double) confidence level (denoted alpha) for the confidence interval about the mean line. Has lower precedence than UpperBoundData and LowerBoundData if specified.
  • UpperBoundData (1 x n numeric vector) upper bound data of the shaded area encapsulating the mean line. By default is set to MeanData + StdDevData unless otherwise specified.
  • LowerBoundData (1 x n numeric vector) The lower bound data of the shaded area encapsulating the mean line. By default is set to MeanData - StdDevData unless otherwise specified.
  • BoundDataMode ('auto' or 'manual') mode describing the method by which the bounds of the shaded area are determined. In 'auto' mode, a confidence interval of level alpha (default 0.05) will be used. In 'manual' mode, the user can specify UpperBoundData and LowerBoundData as Name/Value pairs.
  • Edges (1 x n numeric vector) edges of the bins used to group raw x-data values and generate the center line x-data and y-data. Once grouped, the mean x-value of each bin (excluding NaNs) will be used for CenterXData and the mean y-value of each bin (excluding NaNs) will be used for CenterYData.

Stylistic Name-Value Pair Arguments/Properties

  • TitleText (1 x n char vector) title of the confidence interval plot.
  • SubtitleText n x 1 char vector) subtitle of the confidence interval plot.
  • ShadeColor (1 x 3 numeric vector) color of the shaded area surrounding the mean line.
  • ShadeAlpha (scalar double) transparency (alpha) of the shaded area surrounding the line.
  • CenterLineColor (1 x 3 numeric vector) color of the center line contained in the shaded area.
  • CenterLineWidth (scalar double) width of the center line.
  • BorderLinesColor (1 x 3 numeric vector) color of the two lines outlining the shaded area from above and below.
  • BorderLinesWidth (scalar double) width of the two lines outlining the shaded area about the center line.
  • ShowRawData (scalar matlab.lang.OnOffSwitchState) OnOffSwitchState object indicating whether to plot the original data (XData, YData) as scatter points.
  • RawDataMarker (char) marker symbol for raw data if ShowRawData is true.
  • RawDataMarkerColor (1 x 3 numeric vector) color of data markers for raw data if ShowRawData is true.
  • RawDataMarkerSize (double) size of data markers for raw data if ShowRawData is true.
  • ShowCenterData (scalar matlab.lang.OnOffSwitchState) OnOffSwitchState object indicating whether to plot the original data (CenterXData, CenterYData) as scatter points.
  • CenterDataMarker (char) marker symbol for raw data if ShowCenterData is true.
  • CenterDataMarkerColor (1 x 3 numeric vector) color of data markers for raw data if ShowCenterData is true.
  • CenterDataMarkerSize (double) size of data markers for raw data if ShowCenterData is true.

Example

Create a confidence interval plot for sine data with noise. Each unique x-value is associated with three y-values. By default, the confidence interval is a 95% confidence interval for each unique x-value.

uniqueX = -2 * pi : pi/4 : 2*pi;

x = repelem(uniqueX, 3);
y = sin(x) + 0.5 * rand(size(x));
 
cip = confidenceIntervalPlot(x,y);
cip.NumSteps = 10;

title("95% Confidence Interval Plot, Sine Curve with Random Noise");
subtitle("Alpha = 0.05");

Cite As

Jennie Chung (2021). Confidence Interval Plot (https://github.com/MATLAB-Graphics-and-App-Building/confidenceIntervalPlot/releases/tag/v1.0), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2021a
Compatible with R2021a
Platform Compatibility
Windows macOS Linux
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To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.