TemporalData object can host multiple paths or it can admit a
ValueDimensions option value greater than unity.
In the former case, using the
Values property of the
TemporalData object, produces a list of paths -each list represents a different path- while in the later case, one obtains a single path, but, instead of a single value per time instance (t) in this case, one obtains a list or vector per t.
To make the issue more concrete, consider having $T$ observations. In the former case (many paths, single
ValueDimensions), with a number of $k$ paths, the data in the
TemporaData object have dimensions $k\times T$.
On the other hand, in the later case, setting a
ValueDimensions value equal to
d, yields an underlying data structure with dimensions $T\times d$.
On a first glance there seems to be little in common between the two representation. Consider now what would be the case if it so happened that
d=k. In such a case, it would seem, that the former data representation is the
Transpose of the later (or viceversa). With that occurrence in mind, my question is about making the most out of the
What are some guiding lines on how to represent data using
TemporalData objects? When the time stamps of the values are the same for all paths, aren't the two representations discussed above, equivalent?
Is there a use case where the two representations are not equivalent (for common time stamps between paths)? Has anyone dealt with situations where either of the approaches is strongly preferred to the other ?