Point processes

Related lectures (32)

Poisson Process: Probability Law

Covers the Poisson process, a stochastic model for communications, focusing on the probability law.

Modelling Stochastic Communications: Poisson Process Probability Law

Covers the Poisson process and its probability law in communication systems.

Simulation & Optimization: Poisson Process & Random Numbers

Explores simulation pitfalls, random numbers, discrete & continuous distributions, and Monte-Carlo integration.

Poisson Process: Probability Law

Covers the Poisson process in detail, focusing on the probability law and its applications.

Stochastic Simulation: Markov Processes Generation

Covers the generation of Markov processes and Poisson processes in stochastic simulation.

Point Processes: Spatial Analysis

Explores point processes in spatial analysis, focusing on spatial object dissemination and pattern detection.

Poisson Process: Properties

Covers the properties of Poisson processes, including arrival times and stochastic models for communications.

Poisson Process: Properties

Covers the properties of Poisson processes, including arrival rate and inter-arrival time.

Generation of Markov Processes

Covers the generation of Markov processes and Markov chains, including transition matrices and stochastic matrices.

Mapping and Colouring: Poisson Processes

Covers the theorems of superposition and colouring for Poisson processes.

Multivariate Extremes: Applications and Dependence

Explores multivariate extremes, including overwhelming sea defenses and heat waves.

Poisson Process Theory: Properties and Applications

Explores Poisson process theory, covering properties, applications, and key theorems.

Point Processes: Extremal Limit Theorems

Explores the theory of point processes and their applications to extremes, emphasizing the Laplace functional and Kallenberg's theorem.

Stochastic Models for Communications

Covers stochastic models for communications, focusing on random variables, Markov chains, Poisson processes, and probability calculations.

Estimating R: Marking and Convergence

Covers the estimation of R in Poisson processes, focusing on marking points and convergence.

Markov Chains: Basics and Applications

Introduces Markov chains, covering basics, generation algorithms, and applications in random walks and Poisson processes.

Elements of Statistics: Memorylessness, Stationary Processes, Estimation using MLE

Explores memorylessness in distributions, stationary processes, and estimation using MLE.

Mapping Theorems: Poisson Processes and Intensity Functions

Explores mapping theorems for Poisson processes and their intensity functions.

Poisson Processes and Angular Density

Explores Poisson processes, Pickands' function, and multivariate angular densities.

Poisson Process Approach

Explores the Poisson process approach in extreme value analysis, emphasizing component-wise transformations and likelihood functions for extreme events.