diff --git a/News_For_Wouter/Sep_2018/README.md b/News_For_Wouter/Sep_2018/README.md
index 2e54ee8b33e053e2a9efe05b0a9a15821a9ae0d4..e85c4e780334b574232af2c6c4c45286c4f3a33f 100644
--- a/News_For_Wouter/Sep_2018/README.md
+++ b/News_For_Wouter/Sep_2018/README.md
@@ -69,7 +69,6 @@ be interpreted as an adaptive learning rate.
# g squared (fancy name for changing the sign of the LL)
G2 <- sum(subjectLevel$ProbCorrect, na.rm = TRUE)
G2 <- -2*G2
- #Upper bounds - I also had beta max 1 min -1 as in your script but I wonder could be even more ambig averse so I think larger range is also fine...
G2
}
@@ -138,7 +137,6 @@ estimate of the participants to create logliks.
# g squared (fancy name for changing the sign of the LL)
G2 <- sum(subjectLevel$ProbCorrect, na.rm = TRUE)
G2 <- -2*G2
- #Upper bounds - I also had beta max 1 min -1 as in your script but I wonder could be even more ambig averse so I think larger range is also fine...
G2
}
```
@@ -183,7 +181,6 @@ amount of time.
# g squared (fancy name for changing the sign of the LL)
G2 <- sum(subjectLevel$ProbCorrect, na.rm = TRUE)
G2 <- -2*G2
- #Upper bounds - I also had beta max 1 min -1 as in your script but I wonder could be even more ambig averse so I think larger range is also fine...
G2
}
@@ -309,6 +306,8 @@ fitted Parameters in the same dataFrame
```
+
+
#### Model Comparison
----------------
@@ -337,21 +336,34 @@ Seqential Updating is bad.
# So now lets look at the learning rates.
---------------------------------------
+
+
### Marble Estimate Distribution
+
+
This plot shows how the learning rates are distributed in all subjects.
We can see that most of the subjects seem to overweight new pieces of
information relative to an Ideal observer.
+
+
![](HalfHGF_files/figure-markdown_strict/ShowPlot-1.png)
+
+
### Marble Estimate Distribution Exponential
+
+
What i get now if i look at the parameter estimate
of the exponential model is an **underweghting** of all information
considered.
+
+
![](HalfHGF_files/figure-markdown_strict/Show%20second%20Plot-1.png)
+
## Marble Estimation Distributin HGF_Like
The HGF like model has no Benchmark and the “learning rate" can not be super easily interpreted. But i like it :)