How can I add noise to linear graph

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lucky_
lucky_ 2016-1-21
评论： jgg 2016-1-21
I have 100 sample points and I'm using y=mx+c to create 1d line and add gaussian noise using randn the attached graph is the result that I got when I tried the first code and when I try the second code I get straight line I think there is something wrong with my plot but I'm not sure where ?
code1
sample = 100;
x = linspace(-5,5);
y= 1.6 * x +6;
dataset = randn(sample,2);
figure
plot(dataset,y)
axis([-8 7])
code2
sample = 100;
x = linspace(-5,5);
y= 1.6 * x +6;
dataset = y*randn(sample,2);
figure
plot(dataset)
axis([-8 7]);
this is the result that I want to get

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采纳的回答

jgg
jgg 2016-1-21
编辑：jgg 2016-1-21
You never added the random noise to your dataset:
sample = 100;
x = linspace(-5,5);
y= 1.6 * x +6;
r = randn(2,sample);
figure
plot(x,r(1,:)+y)
hold on
plot(x,r(2,:)+y)
The actual outcome value is y + r(i,:) not just y; you also are plotting it incorrectly before.
  2 个评论
lucky_
lucky_ 2016-1-21
Thanks that worked I'm still new to this so I wasn't sure .. is there function to plot fitted line
jgg
jgg 2016-1-21
Yes. Let's code it up a little more clearly since you want to fit something too:
sample = 100;
x = linspace(-5,5);
y= 1.6 * x +6;
r = randn(2,sample);
y_noise = y + r(1,:);
X = [ones(1,length(x)); x];
beta = regress(y_noise',X');
y_fitted = beta(1) + x*beta(2);
figure
plot(x,y_noise)
hold on
plot(x,y_fitted)
This fits a linear regression curve to the noisy data using the regress function with an intercept. The coefficients are in beta.
If this answer solved your problem, please help others find it by accepting it.

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