Computing estimates in the proportional odds model
نویسندگان
چکیده
In this paper we present an algorithm for maximum likelihood estimation in the proportional odds model. The algorithm is an example of optimization transfer, also known as the method of iterative majorization. We discuss optimization transfer, present the proportional odds algorithm, and give a means for accelerating the convergence of the algorithm. The algorithm is stable and guaranteed to converge to the maximum likelihood estimate when it exists, regardless of the starting points. For large problems, both the algorithm and an accelerated version of it outperform the Newton-Raphson method.
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