Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Monte Carlo EM Algorithm for the Parameter Estimation of Aggregated
  Hawkes Processes   A key difficulty that arises from real event data is imprecision in the
recording of event time-stamps. In many cases, retaining event times with a
high precision is expensive due to the sheer volume of activity. Combined with
practical limits on the accuracy of measurements, aggregated data is common. In
order to use point processes to model such event data, tools for handling
parameter estimation are essential. Here we consider parameter estimation of
the Hawkes process, a type of self-exciting point process that has found
application in the modeling of financial stock markets, earthquakes and social
media cascades. We develop a novel optimization approach to parameter
estimation of aggregated Hawkes processes using a Monte Carlo
Expectation-Maximization (MC-EM) algorithm. Through a detailed simulation
study, we demonstrate that existing methods are capable of producing severely
biased and highly variable parameter estimates and that our novel MC-EM method
significantly outperforms them in all studied circumstances. These results
highlight the importance of correct handling of aggregated data.

24
The categories of this paper are: dg-ga
12
The categories of this paper are: nucl-th
28
The categories of this paper are: alg-geom
27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
17
The categories of this paper are: q-fin
20
The categories of this paper are: acc-phys
31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
32
The categories of this paper are: atom-ph
37
The categories of this paper are: supr-con
2
The categories of this paper are: math
25
The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph