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The Statistics Clinic

Our main research areas include:

  • High-dimensional statistical inference
  • Classification, clustering and regression problems
  • Data perturbation methods (e.g. subsampling, bootstrap sampling, random projections, knockoffs)
  • Time series analysis
  • Functional data analysis
  • Causal inference
  • Large-scale data analysis
  • Nonparametric statistics, e.g. asymptotic theory
  • Shape-constrained estimation problems
  • Changepoint detection and estimation
  • Unconditional and conditional independence testing
  • Random matrix theory
  • Image Analysis
  • Spatial-temporal Statistics
  • Applications, including genetics, archaeology and oceanography

But we are also able to answer general inquiries from (but not limited to) the following areas:

  • Linear models
  • Generalised linear models
  • Mixed effect models
  • Hypothesis testing
  • Missing data
  • Model fitting and selection
  • Monte Carlo methods
  • Data mining
  • Biostatistics, especially survival analysis
  • Bayesian inference
  • Experimental design
  • Convex optimisation
  • Statistical Computing with R
  • ...