X-DataInitiative/tick

The goodness of fit of Hawkes processes (or D-dimentional Hawkes processes)

Opened this issue · 4 comments

Good morning,

I read the paper that tick.HawkesADM4 was developed:
'Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processes.'
For my understanding, this paper focused on optimisation problem, and they use "loglike" metric score to compare with baseline.
So, I am wondering that which function from 'tick' provide me to test whether Hawkes processes fit with my data ( I mean the goodness of fit).
Thank you.

Hi,

Have you tried objective : that is the function to be minimized, or score : that is the goodness of fit function, to test whether Hawkes processes fit with your data but that does not include the penalty terms.

Hi,
Thank you. Yes I have tried. But I don't think it is as we usually do in statistics like, we will test how well Hawkes processes can fit with the data. And,
I am just wondering that is it weird if I got some coefficient values of adjacency matrix are greater than 1? I though the coefficient values of adjacency matrix are in (0,1).
Can you help me to correct me please?
Thank you.

Hi,
Thank you. Yes, I mean p-value.
Re: The entries of the adjacency matrix. So, it doesn't mean the influence probabilities of users in HawkesADM4?
I thought the adjacency matrix as the following paper mentioned:
Zhou, K., Zha, H., & Song, L. (2013, May). Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processes.

I am so sorry to ask a lot. But, I am confused now. Might you help me to clarify, please?
Thank you.