Constrained EM algorithm with projection method
This paper proposes a new step called the P-step to handle the linear or nonlinear equality constraint in addition to the conventional EM algorithm. This new step is easy to implement, first because only the first derivatives of the object function and the constraint function are necessary, and secondly, because the P-step is carried out after the conventional EM algorithm. The estimate sequence produced by our method enjoys a monotonic increase in the observed likelihood function. We apply the P-step in addition to the conventional EM algorithm to the two illustrative examples. The first example has a linear constraint function. The second has a nonlinear constraint function. We show finally that there exists a Kuhn–Tucker vector at the limit point produced by our method. Copyright Springer-Verlag 2012
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 27 (2012)
Issue (Month): 4 (December)
Pages: 701-714
| Handle: | RePEc:spr:compst:v:27:y:2012:i:4:p:701-714 |
| DOI: | 10.1007/s00180-011-0285-x |
| Contact details of provider: | Web page: http://www.springer.com
|
| Order Information: | Web: http://www.springer.com/statistics/journal/180/PS2 |
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Celeux, Gilles & Govaert, Gerard, 1992. "A classification EM algorithm for clustering and two stochastic versions," Computational Statistics & Data Analysis, Elsevier, vol. 14(3), pages 315-332, October.
- Donald Rubin & Dorothy Thayer, 1982. "EM algorithms for ML factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 47(1), pages 69-76, March.
- Sik-Yum Lee & Sin-Yu Tsang, 1999. "Constrained maximum likelihood estimation of two-level covariance structure model via EM type algorithms," Psychometrika, Springer;The Psychometric Society, vol. 64(4), pages 435-450, December.
- Jamshidian, Mortaza, 2004. "On algorithms for restricted maximum likelihood estimation," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 137-157, March.
This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.
When requesting a correction, please mention this item's handle: RePEc:spr:compst:v:27:y:2012:i:4:p:701-714. 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: (Sonal Shukla)
or (Rebekah McClure)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.