Create a Markov-modulated Hawkes Process(MMHP) object

Create a Markov-modulated Hawkes Process(MMHP) model according to the given parameters: lambda0, lambda1, alpha, beta, event times and transition probability matrix. If event time events is missing, then it means that data will be added later(e.g. simulated)

pp_mmhp(lambda0, lambda1, alpha, beta, Q = NULL, delta = NULL, events = NULL)

Arguments

lambda0	intensity for homogeneous Poisson process.
lambda1	base intensity for Hawkes process.
alpha	jump size of the increase in intensity in the hawkes process
beta	exponential decrease of intensity in the hawkes process
Q	transition probability matrix.
delta	initial state probability.
events	vector containing the event times. Note that the first event is at time zero. Alternatively, events could be specified as NULL, meaning that the data will be added later (e.g. simulated).

Value

mmhp object

Examples

Q <- matrix(c(-0.4, 0.4, 0.2, -0.2), ncol = 2, byrow = TRUE)
pp_mmhp(Q,
  delta = c(1 / 3, 2 / 3), lambda0 = 0.9, lambda1 = 1.1,
  alpha = 0.8, beta = 1.2
)
#> Markov Modulated Hawkes Process 
#> lambda0  0.9 
#> lambda1  1.1 
#> alpha  0.8 
#> beta  1.2 
#> Q  -0.4 0.2 0.4 -0.2 
#> delta 0.3333333 0.6666667