Jin_Lee_2021/Matlab_function/GetLinearRegression.m

function [Regression, f] = GetLinearRegression(x,y,varargin)

if isempty(varargin)
    flag=0;
    f=0;
else
    flag=1;
    g = varargin{1};
end

j=1;
for i=1:length(x)
    if ~isnan(x(i)) && ~isnan(y(i))
        x1(j)=x(i); y1(j)=y(i);
        j=j+1;
    end
end
if exist('x1')
    [r, p] = corrcoef(x1,y1);
    Regression.R=r(1,2);
    Regression.Rsquared=r(1,2)^2;
    Regression.Pvalue=p(1,2);

    if flag
        [a] = polyfit(x1,y1,1);
        f=polyval(a,x1);
        [r2, rmse] = rsquare(y1,f);
        Regression.a0=a(2); Regression.a1=a(1); % f(x) = a0 + a1*x
        Regression.x2=[g.XLim(1) g.XLim(2)];
        Regression.y2=Regression.a0+Regression.a1*Regression.x2;
    end
else
    Regression.R=NaN;
    Regression.Rsquared=NaN;
    Regression.Pvalue=NaN;
end
%     p3=plot(x2,y2,'k-');
%     p3.LineWidth=2;
%     deltaY=(g.YLim(2)-g.YLim(1))/10;
%     deltaX=(g.XLim(2)-g.XLim(1))/10;
    
%     t1=text((g.XLim(1)+3*deltaX), (g.YLim(2)-4*deltaY),['p-value : ' num2str(round(Pvalue,3))]);
%     t1.FontSize=fontsize.axis; t1.FontWeight='bold';
%     t2=text((GCA.XLim(1)+3*deltaX), (GCA.YLim(2)-3*deltaY),['r-squared : ' num2str(round(Rsquared,3))]);
%     t2.FontSize=fontsize.axis; t2.FontWeight='bold';
%     t3=text((g.XLim(1)+3*deltaX), (g.YLim(2)-2*deltaY),['r : ' num2str(round(r(1,2),3))]);
%     t3.FontSize=15; t3.FontWeight='bold';    
%