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Download the Paper (285 K, PDF file) - January 1, 2006 Tell a colleague about it. Printing Tips: Select 'print as image' in the Acrobat print dialog if you have trouble printing.

ABSTRACT:
So far, many ad hoc techniques have been proposed to compute maxium likelihood estimates for various specific models. Some work well, some don't. Our purpose in this presentation is to present a general approach based on quadratic majorization. This class of algorithms has the desirable property that it computes maximum likelihood estimates by solving a sequence of least squares problems, which are generally much simpler. It also produces an algorithm which is globally convergent.

SUGGESTED CITATION:
Jan de Leeuw and Jeffrey Lewis, "Principal Component Analysis of Categorical Data, with Applications to Roll-Call Analysis" (January 1, 2006). Department of Statistics, UCLA. Department of Statistics Papers. Paper 2006010101.
http://repositories.cdlib.org/uclastat/papers/2006010101