ciency of NPMLE in Nonparametric Missing Data
نویسندگان
چکیده
Suppose that a random variable X of interest is grouped or censored or missing so that one only observes a coarsening of X, i.e., a random set containing X with probability 1. It is assumed that the coarsening mechanism has the coarsening at random property. Suppose furthermore that the coarsening either equals X itself or that is a set with positive X-probability. We modify the NPMLE of the distribution of X by demanding that its support is the set of observed data points. We provide a general theorem giving suucient conditions for eeciency of this NPMLE, or eeciency of the NPMLE after a small data reduction. We apply the theorem to a number of examples.
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Efficiency of NPMLE in Nonparametric Missing Data Models
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