Exponential trace model for networks of discrete and continuous data
This repository provides an implementation of the sampling-based approximation for computing the maximum likelihood estimator (MLE) of exponential trace model.
Implementation/exp_trace_model.R contains functions for computing the approximate maximum likelihood estimator. Our upcoming paper describes the algorithm in details.
We include an example code
Implementation/example.R for analyzing neuron spike data. The neuron spike data is from Demas et al. 2003.
Running the simulation, as described in the paper, takes a long time and is recommended to be implemented on a cluster. We include small-scale example code in the repository.
Data-type specific functions can be found under
Poisson analog data
Exponential analog data
Composite of Poisson analog and Bernoulli data
Composite of Poisson analog and Gaussian data