function [logp, yhat, res] = tapas_logrt_linear_binary_minimal(r, infStates, ptrans) % Calculates the log-probability of log-reaction times % % -------------------------------------------------------------------------------------------------- % Copyright (C) 2016 Christoph Mathys, UZH & ETHZ % % This file is part of the HGF toolbox, which is released under the terms of the GNU General Public % Licence (GPL), version 3. You can redistribute it and/or modify it under the terms of the GPL % (either version 3 or, at your option, any later version). For further details, see the file % COPYING or . % Transform parameters to their native space be0 = ptrans(1); be1 = ptrans(2); be2 = ptrans(3); ze = exp(ptrans(6)); % Initialize returned log-probabilities, predictions, % and residuals as NaNs so that NaN is returned for all % irregualar trials n = size(infStates,1); logp = NaN(n,1); yhat = NaN(n,1); res = NaN(n,1); % Weed irregular trials out from responses and inputs y = r.y(:,1); y(r.irr) = []; u = r.u(:,1); u(r.irr) = []; % Extract trajectories of interest from infStates mu1hat = infStates(:,1,1); sa1hat = mu1hat.*(1-mu1hat); % Surprise % ~~~~~~~~ m1hreg = mu1hat; m1hreg(r.irr) = []; poo = m1hreg.^u.*(1-m1hreg).^(1-u); % probability of observed outcome surp = -log2(poo); % Bernoulli variance (aka irreducible uncertainty, risk) % ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ bernv = sa1hat; bernv(r.irr) = []; % Calculate predicted log-reaction time % ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ logrt = be0 +be1.*surp +be2.*bernv; % Calculate log-probabilities for non-irregular trials % Note: 8*atan(1) == 2*pi (this is used to guard against % errors resulting from having used pi as a variable). reg = ~ismember(1:n,r.irr); logp(reg) = -1/2.*log(8*atan(1).*ze) -(y-logrt).^2./(2.*ze); yhat(reg) = logrt; res(reg) = y-logrt; end