tick.hawkes.HawkesKernelPowerLaw¶

class tick.hawkes.HawkesKernelPowerLaw(multiplier, cutoff, exponent, support=-1, error=1e-05)[source]¶

Hawkes kernel for power law

$\phi(t) = \phi(t) = \alpha (\delta + t)^{- \beta} 1_{t > 0}$

Where $\alpha$ is called the multiplier, delta the cut-off and $\beta$ the exponent

Parameters

multiplier : float

Multiplier of the kernel, also noted $\alpha$

cutoff : float

Cut-off of the kernel, also noted $\delta$

exponent : float

Exponent of the kernel, also noted $\beta$

__init__(multiplier, cutoff, exponent, support=-1, error=1e-05)[source]¶: Initialize self. See help(type(self)) for accurate signature.

get_norm(n_steps=10000)¶

Computes L1 norm

Parameters: n_steps : int

number of steps used for integral discretization

Notes

By default it approximates Riemann sum with step-wise function. It might be overloaded if L1 norm closed formula exists

get_values(t_values)¶: Returns the value of the kernel for all times in t_values

Examples using `tick.hawkes.HawkesKernelPowerLaw`¶