@@ -9,14 +9,6 @@ under the specific probability estimate of the participant is now the

likelihood that we validate our parameter estimates with. For this i first need a function that returns discrete values for

the probability denisty in question.

I implemented the function you sent to me in your mail. At some point

when you talk about the arguments that you pass to the cumulative

densitiy function which you use to get a log likelihood; you say sigma

is sigma. In the example you sent to me; you do not use sigma as the

variance estimate of the beta updating before. You pass sigma with the

function one higher level that you then minimize. Is sigma as you use it

a free parameter of the model as well? So you dont have one but two free

parameters?

discretenormalMarble005(posResp,model_weight, sigma); % THIS IS THE CUSTOM FUNCTION WE BUILT FOR THIS STEP SEE BELOW (posResp is list made above. I guess of all possible resonses a subject can make).. sigma is sigma..