Matlab Assignment 7
Make the Matalb assignment discussed in the last class (least square regression estimates).
Make sure that you program a function with proper comments and at least one test for sound input.
Test your function with some input vectors, for example: y=[1,2,4,23,4,6,3,2] and x=[5,4,3,2,6,5,4,3] You can take any other input vectors.

m.file command: function [alpha_estimate, beta_estimate] = my_regression(y,x) n = length(x) a = sum(x); b = sum(y); c = sum(x)/n; d = sum(y)/n; e = sum(x.*y); f = sum(x.*x); alpha_estimate = d-(e-n*c*d)/(f-n*c^2)*c; beta_estimate = (e-n*c*d)/(f-n*c^2); disp('alpha =') disp(alpha_estimate) disp('beta =') disp(beta_estimate) % Purpose of the function: This function is used to calculate the
% coefficients of the regression formula.
% Input: value of y and x
% Output: alpha_estimate and beta_estimate
% How to run the function:
% I use n to represent the length of vector x and y
% a to represent the sum of vector x
% b to represent the sum of vector y
% c to represent the avergae of vector x
% d to represent the average of vector y
% e to represent the sum of vector x and y
% f to represent the sum of square of vector x
%then calculating: alpha_estimate = d-(e-n*c*d)/(f-n*c^2)*c;
% beta_estimate = (e-n*c*d)/(f-n*c^2);
% Author: Hengya Jin
% Date of last change: 11/27/2013 end

Check:
>> y=[1,2,4,23,4,6,3,2]
>> x=[5,4,3,2,6,5,4,3]
>> my_regression(y,x) n = 8 alpha = 17.9583 beta = -3.0833 ans = 17.9583