Abstract:
Complex models often have intractable likelihoods, so methods that involve evaluation of the likelihood function are infeasible. The aims of the research are
• to provide a review of the likelihood free methods (e.g., ABC or synthetic likelihood) used in fitting complex models large dataset;
• to use likelihood free methods to make inference on complex models such as random networks models;
• to develop the code for the analysis;
• to apply the model and methods for networks data from economics and finance such as trade, financial flows networks, financial contagion networks;
• to write a final report where methods and results are presented and discussed.
