Point process

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Related lectures (32)

Explores asymptotic independence models for multivariate extremes and their applications in extrapolating probabilities to rare events.

Mapping Theorems: Poisson Processes and Intensity Functions

Explores mapping theorems for Poisson processes and their intensity functions.

Point Processes: Convergence and Gaussian Processes

Covers point processes, convergence criteria, Laplace functionals, Gaussian processes, covariance functions, and intrinsic stationarity.

Extreme Value Theory: Applications to Time Series

Explores Extreme Value Theory applications to time series, discussing extremogram, moving maxima, and rare event threshold sequences.

Stochastic Simulation: Markov Processes Generation

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

Extreme Value Analysis: Applications and Consequences

Explores extremal limit theorems and statistical analysis for analyzing extreme events like Venezuela rainfall and Venice data.

Modelling Stochastic Communications: Poisson Process Probability Law

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

Poisson Process: Properties

Covers the properties of Poisson processes and their applications in communication stochastic models.

Estimating R: Marking and Convergence

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

Poisson Model: Rate Coding

Explores the Poisson model in computational neuroscience, emphasizing rate coding and stochastic spiking.

Extreme Value Time Series: Modelling and Dependence

Explores extremal limit theorems, point processes, and multivariate extremes in extreme value time series modelling, emphasizing the effect of local dependence on extreme values.

Membrane potential fluctuations

Explores stochastic spike arrival and membrane potential fluctuations in single neurons.

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