implementing linear regression for a vector with missing values
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I have two vectors x=[1 NaN 2 3 NaN 4 NaN NaN NaN 5 ]; y=[10 11 11 6 8 9 7 2 29 93 ]; I would like to know if there is a way to fit a linear regression method to the vector and estimate the missing values in x?
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KSSV
2018-4-2
x=[1 NaN 2 3 NaN 4 NaN NaN NaN 5 ];
y=[10 11 11 6 8 9 7 2 29 93 ];
xi = interp1(y(~isnan(x)),x(~isnan(x))) ;
x(isnan(x))= xi ;
p = polyfit(x,y,1) ;
x1 = linspace(min(x),max(x));
y1 = polyval(p,x1);
plot(x,y,'.r') ;
hold on
plot(x1,y1)
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