From 314522464b37214e9b1772bbcf39381cccbce57a Mon Sep 17 00:00:00 2001 From: Rausch Date: Thu, 10 Oct 2024 10:19:05 +0200 Subject: [PATCH] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 8468b61..73c1b20 100644 --- a/README.md +++ b/README.md @@ -113,8 +113,8 @@ are not assumed to be constant, but instead they are affected by noise drawn fro a lognormal distribution. In each trial, $\theta_{-1,i}$ is given by $c - \epsilon_i$. Likewise, $\theta_{1,i}$ is given by $c + \epsilon_i$. The noise $\epsilon_i$ is drawn from a lognormal distribution with -the location parameter $\mu_{R,i} = \log(\left| \theta_{R,i} - c\right|)$. Continue here. -$\mu_{R,i} =\log(\left|\overline{\theta}_{R,i}- c\right|) - 0.5 \times \sigma^{2}$ and +the location parameter $\mu_{R,i} = \log(\left| \theta_{R,i} - c\right|)- 0.5 \times \sigma^{2}$. Continue here. +$\mu_{R,i} =\log(\left|\overline{\theta}_{R,i}- c\right|) $ and scale parameter $\sigma$. $\sigma$ is a free parameter designed to quantify metacognitive ability. It is assumed that the criterion noise is perfectly correlated across confidence criteria, ensuring that the confidence criteria