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- %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)
- 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-');
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