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Updated: Dec 10, 2025

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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
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Middle censoring in the multinomial distribution with applications
S Rao Jammalamadaka1, Sudeep R Bapat2
1Department of Statistics and Applied Probability, University of California, Santa Barbara, USA.
Abstract:
In a multinomial set-up with k possible outcomes, we develop estimation under a "middle censoring" paradigm, which is as defined in Jammalamadaka and Mangalam (2003). This problem has many special features because of the inter-dependent probabilities, which we explore here.
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