Web image prediction using multivariate point processes
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Accelerating parameter estimation for multivariate self-exciting point processes
Proceedings of the 2014 ACM/SIGDA international symposium on Field-programmable gate arrays
| Hi-index | 754.84 |
A simple and efficient method of simulation is discussed for point processes that are specified by their conditional intensities. The method is based on the thinning algorithm which was introduced recently by Lewis and Shedler for the simulation of nonhomogeneous Poisson processes. Algorithms are given for past dependent point processes containing multivariate processes. The simulations are performed for some parametric conditional intensity functions, and the accuracy of the simulated data is demonstrated by the likelihood ratio test and the minimum Akaike information criterion (AIC) procedure.