forecast method: support for time series with different datestamps

[AzulGarza]

Is your feature request related to a problem? Please describe. Right now the forecast method assumes:

• All series end with the same timestamp.
• The datestamp column (ds) of the input dataframe (Y_df) is a well-formatted string.

To train a model these assumptions are not necessary. (A user can train using ints or floats as the ds column).

Describe the solution you'd like Consider these scenarios in the forecast method.