Create function that functionally same to polyfit

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종석 박
종석 박 2022 年 5 月 16 日
編集済み: 종석 박 2022 年 6 月 9 日 11:55
Create a user-defined function 'fitpoly' that has the same function as 'polyfit'
Reads the given data points from a text or Excel file and approximates the curve with an nth-order polynomial function
Set the input and output factors the same as ‘polyfit’
  4 件のコメント
Sam Chak
Sam Chak 2022 年 5 月 17 日
I think the Professor won't penalize @종석 박 so long as he acquired the regression analysis knowledge (cognitive) and the coding skills (psychomotor) as required by the assignment and outlined in the Outcome-Based Education (OBE). The Professor will be happy when writing the Education Report at the end of the academic term. As long as there is no blatant plagiarism elements, then he should be "SAFE".
Nevertheless Park will still have to produce the math as shown in Polynomial Regression.


回答 (3 件)

Image Analyst
Image Analyst 2022 年 5 月 17 日
There is still another way @종석 박 can do the assignment without plagiarizing. He can construct the equation like
Ax = y
using a for loop where A =
x(1)^n, x(1)^(n-1), x(1)^(n-2), ....., x(1), 1
x(2)^n, x(2)^(n-1), x(2)^(n-2), ....., x(2), 1
x(3)^n, x(3)^(n-1), x(3)^(n-2), ....., x(3), 1
x(m)^n, x(m)^(n-1), x(m)^(n-2), ....., x(m), 1
Then once you have the tall array you can do
coefficients = A \ y(:)
which is basically the method for doing least squares regression "manually".

Sam Chak
Sam Chak 2022 年 5 月 16 日
I find it a little strange. Should your Intructor/Professor send you to learn the essentials through MATLAB Onramp at the beginning of the course in MATLAB?
From your description, it seems that your Intructor/Professor wants you to study the algorithm in polyfit.m.
This example only has 3 points, (1, 4), (2, 7), (3, 14). Try to improvise from here.
% Formulate the problem as a linear equation, A*x = b
P = [1 4; 2 7; 3 14]
x = P(:, 1)
A = [x.^2 x repelem(1, 3, 1)]
b = P(:, 2)
x = A\b

Image Analyst
Image Analyst 2022 年 5 月 16 日
@종석 박 did you try what Jan told you?
function coefficients = myPolyFit(x, y, n)
coefficients = x(:) .^ (n : -1 : 0) \ y(:);
If not, why not?

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