Johns Hopkins University 3 credits Applied Mathematics & Statistics
This course will cover the basic theory of point processes in Euclidean space and introduce a range of stochastic geometric models built from point processes and random closed sets. Example topics to be covered include: point processes as random counting measures, stationarity of point processes, Palm theory, Poisson point processes, Cox processes, determinantal point processes, Boolean models, processes of flats, and random tessellations. Point processes and stochastic geometry models have been used to model random spatial patterns in a range of applications including physics, machine learning, image analysis, information theory, networks, wireless communications, biology, ecology, seismology, and cosmology.
Our subject experts help with essays, research papers, case studies, discussion posts, and capstone projects for these programs β written from scratch to your course requirements.
Program and course information is reproduced from each university's published academic catalog for informational purposes and may change. Always confirm current requirements with your university. We are an independent academic support service and are not affiliated with or endorsed by the universities listed.
Expert guides on essay writing, citation styles, study skills, and academic success.
View All Articles
Learn how to write a good research question for a paper. Narrow your topic, identify a research problem, and create a focused question with practical examples.
Learn how to choose a research topic you can actually research. Discover how to narrow broad ideas, find reliable sources, and develop a focused research question.
Learn how to cite sources in a research paper using APA, MLA, and Chicago styles, with in-text citation examples and reference-list tips.