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“Poisson Processes” as a book category comprises works on the theory and applications of Poisson point processes—stochastic models for random events occurring in time or space with independent increments and (in the homogeneous case) exponentially distributed interarrival times. Titles range from introductory textbooks to advanced monographs and application-driven guides, covering core concepts such as counting processes, stationarity, thinning and superposition, nonhomogeneous and marked variants, spatial Poisson processes, and connections to renewal theory and queueing. Many books emphasize statistical inference and modeling—estimating intensities, testing model fit, and simulating event streams—alongside real-world case studies in telecommunications, reliability and survival analysis, operations research, insurance and risk, finance, neuroscience, seismology, epidemiology, and spatial statistics. This category serves students, researchers, and practitioners in probability, statistics, data science, engineering, and related fields who need both rigorous foundations and practical modeling tools.

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