A new identification and stochastic-EM estimation framework for causal effects in spatiotemporal point processes with outcome spillover and carryover, using latent superposition of control and treatment components.
Throughout the analysis, we index complete-data likelihoods and intensities by a labelling r= (r i)i≥1 ∈ {0,1} N
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Causal inference for spatiotemporal point processes in the presence of outcome spillover and carryover
A new identification and stochastic-EM estimation framework for causal effects in spatiotemporal point processes with outcome spillover and carryover, using latent superposition of control and treatment components.