AstroML notebooks

Content

• Chapter 3: Probability and Statistical Distributions
  • Univariate Distribution Functions
• Chapter 5: Bayesian Statistical Inference
  • Parameter Estimation for a Gaussian Distribution
  • Parameter Estimation for a Binomial Distribution
  • Parameter estimation for the Cauchy (Lorentzian) distribution
  • Approximate Bayesian Computation Example
  • Hierarchical Bayes Example
• Chapter 6: Searching for Structure in Point Data
  • Density Estimation for SDSS “Great Wall”
  • Searching for Structure in Point Data
  • Gaussian Mixture Models Example
  • Extreme Deconvolution
• Chapter 7: Dimensionality and its Reduction
  • Dimensionality reduction
• Chapter 8: Regression and Model Fitting
  • Measurement Errors in Linear Regression
  • Measurement errors in both dependent and independent variables
• Chapter 9: Classification
  • Classification
  • Deep Learning: Classifying Astronomical Images
• Chapter 10: Time Series Analysis
  • Modeling Toolkit For Time Series Analysis
  • Wavelets
  • Digital Filtering
  • Temporally localized signals
  • Matched Filter Chirp Search
  • Analysis of Stochastic Processes

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