need help to plot smooth of 𝑦̂ the least-squares fit to the data, over the range of x-values

function [coefficients, MSE] = pnnnfit(x, y, order)
coefficients = polyfit(x, y, order)
y_fitted = polyval(coefficients, x)
squaredError = (y - y_fitted) .^ 2
MSE = sum(squaredError)
plot(x, y,'o')
end
%x=[0 .5 1 1.5 2 2.5 3 3.5 4 4.5 5];
%  y=[0 -5.27 -8.10 -8.46 -6.38 -1.84 5.15 14.59 26.48 40.83 57.63];

[KSSV]

Read about interp1.

Answer 1

[Ameer Hamza]

You are just plotting the actual points. The y_fitted will be smooth

x=[0 .5 1 1.5 2 2.5 3 3.5 4 4.5 5];
y=[0 -5.27 -8.10 -8.46 -6.38 -1.84 5.15 14.59 26.48 40.83 57.63];
pnnnfit(x, y, 2);

function [coefficients, MSE] = pnnnfit(x, y, order)
    coefficients = polyfit(x, y, order)
    y_fitted = polyval(coefficients, x)
    squaredError = (y - y_fitted) .^ 2
    MSE = sum(squaredError)
    plot(x, y,'o')
    hold on
    plot(x, y_fitted)
end