Focused 2x2 Markovian vs non-Markovian Hawkes comparison

Fits the four (kernel, baseline) combinations corresponding to the two endpoints of the Kwan-Chen-Dunsmuir framework: classical exponential / constant Markovian, against gamma / sinusoidal non-Markovian. Faster to run than the full 8-way comparison and suitable for dashboard surfaces.

Usage

morie_tps_hawkes_markovian_vs_nonmarkovian(
  df,
  ds_name = "?",
  max_n = NULL,
  method = "auto",
  eps = 1e-09
)

Arguments

df

Data frame with OCC_DATE or REPORT_DATE.

ds_name

Dataset name used in titles.

max_n

Maximum events to fit; NULL (the default) keeps every event.

method

Likelihood route, as in morie_tps_hawkes_advanced_fit.

eps

Error level of "soe" and "truncate".

Value

A morie_rich_result from morie_tps_compare_hawkes_kernels restricted to the 2x2 sub-grid.

References

Kwan TKJ, Chen F, Dunsmuir WTM (2024). arXiv:2408.09710.

Examples

# \donttest{
  df <- morie_tps_load_tps_dataset("Assault", nrows = 200)
#> morie_tps: no local TPS cache for 'Assault'; using the bundled sample from rmoriedata. Fetch the full export with morie_tps_fetch_category().
  rr <- morie_tps_hawkes_markovian_vs_nonmarkovian(df,
                                                    ds_name = "Assault")
# }