The EMMIX Algorithm for the Fitting of Normal and t-Components
We consider the fitting of normal or t-component mixture models to multivariate data, using maximum likelikhood via the EM algorithm. This approach requires the initial specification of an initial estimate of the vector of unknown parameters, or equivalently of an initial classification of the data with respect to the components of the mixture model under fit. We describe an algorithm called EMMIX that automatically undertakes this fitting: including the provision of suitable initial values if not supplied by the user. The EMMIX algorithm has several options, including the option to carry out a resampling-based test for the number of components in the mixture model.
When requesting a correction, please mention this item's handle: RePEc:jss:jstsof:04:i02. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.