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

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(lamb

[R] Example for multivariate hawkes distribution

Hi, I have a list of N categories that a user can click on. Lets say there are K such users totally. I have the past 3 months data which tells which user has clicked on which category on which date for how many times. For ex - {20th June 2016 : [10,15,12,15]} this dict is for a particular user and