Boris Béranger
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  • Honours Students
    • 2019
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  • Industry Projects
    • Reducing Indigenous contact with the court system.
    • SIGMA Project: Modelling of the reliability of cast iron gas pipes in the Paris region.
  • Masters Students
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  • PhD Students
    • Dr Thomas Whitaker
    • Dr Prosha A. Rahman
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    • Dr Peng Zhong
  • Publications
    • ExtremalDep: Modelling extremal dependence in high-dimensional extremes
    • Analysing symbolic data by pseudo-marginal methods
    • Fast and flexible inference for spatial extremes
    • The influence of neighbourhood disadvantage on charge dismissal: the case of drunk driving
    • Improving population-level refractive error monitoring via mixture distributions
    • New models for symbolic data analysis
    • Likelihood-based inference for modelling packet transit from thinned flow summaries
    • High-dimensional inference using the extremal skew-t process
    • Estimation and uncertainty quantification for extreme quantile regions
    • Logistic regression models for aggregated data
    • Composite likelihood methods for histogram-valued random variables
    • Constructing likelihood functions for interval-valued random variables
    • Extremal properties of the multivariate extended skew-normal distribution, Part B
    • Extremal properties of the univariate extended skew-normal distribution, Part A
    • Tail density estimation for exploratory data analysis using kernel methods
    • Models for Extremal Dependence Derived from Skew-symmetric Families
    • Extreme Dependence Models
  • Recent & Upcoming Talks
    • Fast and flexible inference for spatial extremes
    • Advances in data analysis using aggregated data
    • Logistic Regression Models for Aggregated Data
    • Logistic Regression Models for Aggregated Data
    • Fitting max-stable processes to high-dimensional data
    • Using symbolic data to understand underlying data behaviour
    • Estimation and uncertainty quantification for extreme quantile regions
    • Fitting models to underlying data using aggregates
    • High-dimensional inference for max-stable processes
    • Estimation and uncertainty quantification for extreme quantile regions
    • High-dimensional inference for max-stable processes
    • Composite likelihood and logistic regression models for aggregated data
    • Estimating Equations for Data Summaries
    • Advances in the analysis of aggregated data
    • New Models for Symbolic Data
    • Inference for extremal-$t$ and skew-$t$ max-stable models in high dimensions
    • First steps in the analysis of Symbolic Data
    • A composite likelihood based approach for max-stable processes using histogram-valued variables
    • On some features of the skewed families of max-stable processes
    • Exploratory data analysis of extreme values using non-parametric kernel methods
  • Supervision
  • Teaching
    • _index-old
    • AMSI Summer School 2022
    • DATA9001
    • MATH3841
    • MATH5805
    • MATH5806
    • MATH5856
    • ZZSC5806
    • ZZSC9001

MATH5806

· 0 min read
Last updated on Aug 12, 2025
Boris Béranger
Authors
Boris Béranger
Senior Lecturer
← MATH5805 Jan 1, 0001
MATH5856 Jan 1, 0001 →

© 2025 Boris Béranger. This work is licensed under CC BY NC ND 4.0

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