[R] EM algorithm for maximizing the likelihood of Multivariate Hawkes process

[Ramkishore Swaminathan]

I am trying to model data with multivariate Hawkes distribution. Take the
below example. I am able to compute likelihood but don't know how to
maximize it.

library(hawkes)
lambda0 <- c(0.2,0.2)
alpha   <- matrix(c(0.5,0,0,0.5),byrow=TRUE,nrow=2)
beta    <- c(0.7,0.7)
history <- simulateHawkes(lambda0,alpha,beta,3600)
l       <- likelihoodHawkes(lambda0,alpha,beta,history)

How do I maximize this likelihood so that I can find the best lambda, alpha
and beta parameters?

I am not able to find any library or function calls for doing this.

Thanks for the help.

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