Code for Multiple Continuous Variables

Python notebooks for all the computational examples about Multiple Continuous Variables from Chapter 5 of the book. See here for the full code repository.

  • Temperature in Manhattan and Versailles. Joint probability density function, marginal distribution, conditional distribution
  • More temperature data. Joint probability density function, marginal distribution, conditional distribution, conditional independence
  • Anthropometric data. Joint probability density function, kernel density estimation, Gaussian random vectors, maximum likelihood, parametric and nonparametric models
  • 2D kernel density estimation.
  • Movie duration and earnings. Joint probability density function, conditional pdf, independence
  • Conditional distribution of Gaussian random variables.
  • Eigendecomposition analysis of multivariate Gaussian distribution.
  • Exotic fruit. Gaussian random vectors
  • Simulating a lake. Inverse-transform sampling, dependence between random variables
  • Simulating a triangle.
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    • Estimation of Population Parameters
    • Hypothesis Testing
    • PCA and Low-Rank Models
    • Regression and Classification
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