generate random sample for linear regression
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Hi guys
can anyone help me how to generate random sample for y, x1 and x2 in the following model (multiple linear regression):
yi= a + bx1 + cx2 + e
where a, b and c are parameters and e is random error.
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Jeff Miller
2020-7-17
% First you have to define the characteristics of x1, x2, and e.
% These can be any values you want, such as:
mu1 = 0; % Mean of x1
sd1 = 1; % Standard deviation of x1
mu2 = 100;
sd2 = 10;
rhoxy = 0.3; % the true correlation of x1 and x2
mue = 0; % Mean of e, usually assumed to be zero
sde = 5; % Standard deviation of e
a = 4; % Known parameters of your regression model
b = 3;
c = 2;
nPoints = 100; % the number of data rows you want to generate
% The rest just uses those values:
mu = [mu1, mu2];
sigma = [sd1^2 sd1*sd2*rhoxy; sd1*sd2*rhoxy sd2^2];
x = mvnrnd(mu,sigma,nPoints);
e = mue + sde*randn(nPoints,1);
y = a + b*x(:,1) + c*x(:,2) + e;
更多回答（1 个）
Abhishek Gangwar
2020-7-16
0 个投票
You can generate random values for x1, x2 using "randperm()" function and then find out corresponding 'y' values,
x1 = randperm(100);
x2 = randperm(100);
and put these values into your equation to find out corresponding 'y' values.
Note: 'randperm()' function gives you the random permutation of number from 1....n.
other functions, for example 'rand()', 'randn()' generates decimal numbers.
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