matdiff

%SIMULATION OF THE DIFFUSION PROCESS
rtn=500; %num trials
global rt;
rt=zeros(2,rtn);

maxWalk=15000;

%PARAMETERS
a=10; %positive boundary (the negative is 0)
z=0;  %starting point
s=1;%variance in drift rate within trial
v=0.38;%mean drift rate

for xx=1:rtn
    timeseries(1:maxWalk,1)=NaN;
    timeseries(1)=z;

    for i=2:maxWalk
        timeseries(i)=timeseries(i-1)+normrnd(v,s,1,1);
        if (timeseries(i)>=a)
        %linear interpolation
            slope=timeseries(i)-(timeseries(i-1));
            x=i-(timeseries(i)-a)/slope;
            rt(1,xx)=x;
            break;
        end

    end
    if xx==1
        plot([0 150],[1 1],'b:');
    end
    timeseries(isnan(timeseries))=[];
    time=(1:length(timeseries));
    figure(1); hold on; plot(time, timeseries,'r.-'); drawnow;
end


figure();
RT{1}=rt(1,find(rt(1,:)>0));

%{
[~,~,~,~,~,~,~,par]= myHist(RT{1},'binW',1, 'typePlot','h','fit','invg');
 par{1}{1}
%}
mu=a/v; sig=a.^2./s.^2;
%display(['Estimated - mu:' num2str(par{1}{1}(1)) ' s:  ' num2str(par{1}{1}(2))]);
display(['Real - mu:' num2str(mu) ' s:  ' num2str(sig)]);

x=0:0.1:400;
hold on; plot(x,invgpdf(x,mu,sig),'r-');