It has been shown by Takahashi (2016) that exponential discounting of logarithmic scaled time (i.e. Weber's Law)
t(delay) = b.In(1+a.delay)
is equal to this hyperboloid discount function
1/(1+a.delay)^(k.b)
We cannot identify k.b on a discounting only experiment, and the hyperboloid discount function we use is
1/(1+a.delay)^S
and so the corresponding inferred subjective time function is
t(delay) \propto S.In(1+a.delay)
[x] The Hyperboloid class should be moved to be a subclass of SubjectiveTimeModel
[x] We also need a SubjectiveTimeWebber class (subclass of DiscountFunction) so that we get this Weber's Law plotted in the 'experiment' multi panel plot
It has been shown by Takahashi (2016) that exponential discounting of logarithmic scaled time (i.e. Weber's Law)
is equal to this hyperboloid discount function
We cannot identify
k.b
on a discounting only experiment, and the hyperboloid discount function we use isand so the corresponding inferred subjective time function is
Hyperboloid
class should be moved to be a subclass ofSubjectiveTimeModel
SubjectiveTimeWebber
class (subclass ofDiscountFunction
) so that we get this Weber's Law plotted in the 'experiment' multi panel plot