Point Processes: Spatial Analysis

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Related lectures (32)

Poisson Process: Density Theory and Applications

Explores Poisson processes, joint density, independence of events, and likelihood estimation.

Poisson Process Theory: Properties and Applications

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

Gaussian Process: Covariance and Correlation Functions

Explores Gaussian processes, covariance functions, intrinsic stationarity, and extreme applications in statistics.

Statistical Analysis of Multivariate Extremes

Covers the statistical analysis of multivariate extremes, including extremal limit theorems and models for extremes of time series.

Poisson Process: Properties

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

Vector-Vector Integration: Methods and Tools

Explores methods and tools for integrating vector layers in QGIS, including SQL queries and boolean operators.

Extreme Value Theory: Return Level Estimation

Explores extremal limit theorems, return level estimation, clustering consequences, and modelling strategies for extreme value theory.

Urban Morphology and Morphogenesis

Explores urban morphology, self-organized urban systems, challenges in achieving the (Urban) Digital Twin concept, LASIG's spatial analysis contributions, and teaching geomatics.

Discrete variables: Geometric properties

Covers geometric properties of discrete variables in GIS, including location, size, and shape.

Digital Urban History: QGIS Practical Session

Covers the practical use of QGIS for spatial data analysis and visualization, including georeferencing historical maps and manipulating vector data.

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.

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