Poisson Process Approach

Related lectures (31)

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Explores statistical applications of threshold exceedances and GPD modeling in extreme value theory.

Covers the application of extreme value theory to point processes and the estimation of extreme events from equally-spaced time series.

Covers the theory of Poisson processes and the estimation of the intensity parameter R.

Discusses important theorems related to Poisson processes and their applications in analyzing exceedances and likelihood.

Introduces Maximum Likelihood Estimation in econometrics, covering principles, properties, applications, and specification tests.

Explores maximum likelihood inference, comparing models based on likelihood ratios and demonstrating with a coin example.

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

Covers jacamar data analysis, smoking data models, and challenges with log-linear models in visual impairment data.

Explores maximum likelihood estimation and multivariate hypothesis testing, including challenges and strategies for testing multiple hypotheses.

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