Constrained Maximum Likelihood
Constrained Maximum Likelihood (CML), developed at Aptech Systems, generates maximum likelihood estimates with general parametric constraints (linear or nonlinear, equality or inequality), using the sequential quadratic programming method. CML computes two classes of confidence intervals by inversion of the Wald and likelihood ratio statistics, and by simulation. The inversion techniques can produce misleading test sizes, but Monte Carlo evidence suggests this problem can be corrected under certain circumstances. Citation Copyright 1997 by Kluwer Academic Publishers.
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): 10 (1997)
Issue (Month): 3 (August)
|Contact details of provider:|| Web page: http://www.springer.com|
|Order Information:||Web: http://www.springer.com/economics/economic+theory/journal/10614/PS2|
When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:10:y:1997:i:3:p:251-66. 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 references are entirely missing, you can add them using this form.