How do I Plot a Regression Line (not simple regression) on gscatter?

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Austin Davis 2022-6-22

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评论： Jeff Miller 2022-7-7

I have a scatter plot that I made in gscatter. I wish to add a regression line (which I already have paremeters such as slope for calculated). I can't add a simple regression line (as most existing code and examples use) as I need a Model II regression (I have code for this, to calculate slope, y-intercept, etc.), but I am unsure how to add a Model II regression line, given that I have the slope, etc., onto this gscatter plot. Does anyone have any idea as to possible solutions?

Thank you for your time.

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Answer 1

Jeff Miller 2022-6-23

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在 MATLAB Online 中打开

Something like this should work, after your gscatter:

lowX = 0;   % set low & hi X to span the x-axis range that you want the line to cover.
hiX = 100;
predYatlowX = intercept * slope*lowX;  % using the slope & intercept values from your model
predYathiX = intercept * slope*hiX;
hold on
plot([lowX, hiX],[predYatlowX, predYathiX],'-')

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Austin Davis 2022-6-27

编辑：Austin Davis 2022-6-28

在 MATLAB Online 中打开

Unfortunately I am not able to see the plotted line. I believe it may be out of bounds but I am unsure why.

EDIT: I zoomed out using the low and high X, and I was able to see the trendline. However, it's patently incorrect. I will have to revisit.

EDIT 2: I am now no longer able to do this in order to see the plotted line. "data1" for the line also appears as white, meaning on multiple levels I am unable to see anything. I think I may have better luck with a slightly different Model II regression code but I am unable to ascertain it because "data1" is white.

Here is the full code I am using.

x = Ratio.VariableA;
y = Ratio.VariableB;
g = {Ratio.Category, Ratio.Temperature};
colororder([1 1 1; 0 1 1]); 
gscatter(x, y, g, 'grcm', 'o^s+d', 8, 'on', 'VariableA', 'VariableB')
legend('Location','northeastoutside')
lowX = 0;   % set low & hi X to span the x-axis range that you want the line to cover.
hiX = 0.5;
predYatlowX = b * m*lowX;  % using the slope & intercept values from your model
predYathiX = b * m*hiX;
hold on
plot([lowX, hiX],[predYatlowX, predYathiX],'-')

Austin Davis 2022-7-6

I tried using a different means of calculating the Model II Regression and got a slope of ~12, to the same results or lack thereof. Is there another way in terms of code that I could proceed where I may have better luck with visualization?

Jeff Miller 2022-7-7

在 MATLAB Online 中打开

It's a little hard to suggest anything without seeing your code or data. Here is a small code snippet illustrating one approach to the problem (as I understand it). Maybe it will help to have a little example...

% Example code illustrating one way to plot line over a
% scattergram produced by gscatter
% Make up some random-ish data for two groups
X = 2 + randn(20,1);
Y = 4*X + 5*randn(20,1);
G = repmat([1;2],10,1);
G = G(randsample(G,20));  % Randomly permute the groups to make it look more realistic
% Plot the data with gscatter
figure;
gscatter(X,Y,G)
% Estimate the slope and intercept.
% You said you did this with the command
%  [m,b,r,sm,sb] = lsqfitma(X,Y)
% but I don't know this function so I just
% picked some arbitrary values.
intercept = 0;
slope = 4;
% Compute predictions from the estimated slope & intercept
lowX = 0;   % set low & hi X to span the x-axis range that you want the line to cover.
hiX = 21;
predYatlowX = intercept + slope*lowX;  % using the slope & intercept values from your model
predYathiX = intercept + slope*hiX;
% Add the predicted line to the graph
hold on
plot([lowX, hiX],[predYatlowX, predYathiX],'-')