Abstract
The efficiency of estimation depends not only on the method of estimation but also on the distribution of data. In statistical experiments, statisticians can at least partially design the data-generating process to obtain high estimation performance. This paper proposes a necessary condition for a semiparametrically efficient experimental design. We derived a formula to determine the efficient distribution of the input variables. The paper also presents an application to the optimal bid design problem of contingent valuation survey experiments.
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Tanaka, H. (2021). A Necessary Condition for Semiparametric Efficiency of Experimental Designs. In: Nielsen, F., Barbaresco, F. (eds) Geometric Science of Information. GSI 2021. Lecture Notes in Computer Science(), vol 12829. Springer, Cham. https://doi.org/10.1007/978-3-030-80209-7_77
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DOI: https://doi.org/10.1007/978-3-030-80209-7_77
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