Add trend line to a scatter plot

Hi, I'm ploting some data in a scatter and I want to add a trending line to the plot, but the imput x and y for the scatter are vectors and the fit function take x and y as matrix, how can I do this, my code below:

vec= [-180, -90, 0, 90, 180]
x_mean= randi (1000, 3, 5)
for i= 1:3
hold on
scatter (vec, x_mean (i, :), 'b')
end

I want to add one trend line that consider ALL of the values in the scatter. Need help. Thanks

[Adam Danz]

A trend line (like lsline) is usually understood as a regression line and it would definitely not connect all of the values in the scatter. So, is a trend line really what you want?

You could use plot(vect, x_mean) to connect the series of lines but that would result in 3 lines since there are 3 rows in x_mean.

[Beatriz Sanchez]

I don't want to exactly connect them, I want a trend line that consider all of them

Answer 1

[Adam Danz]

Use coef = polyfit(x,y) to compute the regression coefficients. Then use refline(coef(1),coef(2)) to plot the regression line.

 coef = polyfit(repmat(vec, size(x_mean,1), 1), x_mean, 1);
 h = refline(coef(1), coef(2));

Alternatively, you can use lsline(ax) to add the least squares regression line to each set of data within the axes without needing to compute the regression coefficients.