MATLAB File Help: dml.slda

  slda shrinkage linear discriminant analysis.
 
    DESCRIPTION
    Uses shrinkage to estimate covariance matrices:
    'diaguneq' : Target D of Schafer and Strimmer; Software of Strimmer,
                 covshrinkKPM(X(Y==k,:),0) would give the same result
                 (default)
    'diagcommon' : Target B of Schafer and Strimmer as in Blankertz et al 
 
    REFERENCE
    J. Schafer and K. Strimmer (2005) A Shrinkage Approach to Large-Scale
    Covariance Matrix Estimation and Implications for Functional Genomics
   
    Blankertz B, Lemm S, Treder M, Haufe S, Müller K-R. Single-Trial
    Analysis and Classification of ERP Components - a Tutorial. Neuroimage.
    2010
 
    Opgen-Rhein R, Strimmer K. Accurate ranking of differentially
    expressed genes by a distribution-free shrinkage approach. Stat Appl Genet Mol Biol. 2007;6:Article9. 
 
    EXAMPLE
 
    NOTE
    The approach by Opgen-Rhein may also be of use (see covshrinkKPM)
 
    DEVELOPER
    Marcel van Gerven (m.vangerven@donders.ru.nl)

Superclasses	dml.method
Sealed	false
Construct on load	false

Sigma	covariances
Sinv	inverse of joint covariance matrix
indims	dimensions of the input data (excluding the trial dim and time dim in time series data)
lambda	regularization parameter (automatically determined)
mu	means
pi	priors
restart	when false, starts at the previously learned parameters; needed for online learning and grid search
shrinkage	'diaguneq' or 'diagcommon'
verbose	whether or not to generate diagnostic output

	model	this method does not return a model
	test	compute discriminant functions d
	train