How do I use MatLab to find a line of best fit with a predetermined y intercept using regression.
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I have data on changes in cardiac output with temperature changes from several studies. This data is expressed as CO at Tn / CO at T0, so at baseline temperature the result = 1. I want to find a line of best fit for this data, but the y intercept must be 1 for it to make sense.
How do I use Matlab find a line of best fit with least squares regression for this data, with the y intercept constrained to 1? It is easily done with Microsoft Excel, but I am trying to become more familiar with stats on Matlab.
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Star Strider
2022 年 12 月 18 日
Perhaps —
x = 0:250;
y = randn(size(x));
B0 = x(:) \ (y(:)-1)
fitline = x(:) * B0 + 1;
figure
plot(x, y, '.')
hold on
plot(x, fitline, '-r')
hold off
grid
.
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Star Strider
2022 年 12 月 18 日
My pleasure!
If my Answer helped you solve your problem, please Accept it!
.
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