### Mixture Model Examples and Complements (Advanced Data Analysis from an Elementary Point of View)

Precipitation in Snoqualmie Falls revisited. Fitting a two-component
Gaussian mixture; examining the fitted distribution; checking calibration.
Using cross-validation to select the number of components to use. Examination
of the selected mixture model. Suspicious patterns in the parameters of the
selected model. Approximating complicated distributions vs. revealing hidden
structure. Using bootstrap hypothesis testing to select the number of mixture
components. The multivariate Gaussian distribution: definition, relation to
the univariate or scalar Gaussian distribution; effect of linear
transformations on the parameters; plotting probability density contours in two
dimensions; using eigenvalues and eigenvectors to understand the geometry of
multivariate Gaussians; estimation by maximum likelihood; computational aspects,
specifically in R.

PDF, R; bootcomp.R
(patch graciously provided by Dr. Derek Young)

Advanced Data Analysis from an Elementary Point of
View

Posted at April 09, 2011 23:51 | permanent link