preprocess

An n by p data matrix which is to be scaled.

An optional p by 2 matrix where the columns represent
the sample mean and sample standard deviation of the pth dimension of <code>Y</code>.

If 1, the data is shrunk according to <code>ppp</code>. If 0, the data is expanded
to invert a prior shrinking by <code>ppp</code>.

shrinkQ

Performs the pre-processing of a data matrix such that it is ready
to be used by <code>vbmfa</code>.

Provides methods for fitting the Mixture of Factor Analyzers (MFA) model automatically.
The MFA model is a mixture model where each sub-population is assumed to follow the Factor Analysis model. The Factor Analysis (FA) model is a latent variable model which assumes that observations are normally distributed, but imposes constraints on their covariance matrix. The MFA model contains two hyperparameters; g (the number of components in the mixture) and q (the number of factors in each component Factor Analysis model). Usually, the Expectation-Maximisation algorithm would be used to fit the MFA model, but this requires g and q to be known. This package treats g and q as unknowns and provides several methods which infer these values with as little input from the user as possible.

preprocess: Preprocess

Description

Usage

Arguments

Value

References

See Also

Examples