Abstract
The present chapter studies the famous Neyman–Scott problem, where the number of unknown parameters increases in proportion to the number of observations.
The original version of this chapter was revised: The incomplete texts have been updated. The correction to this chapter is available at https://doi.org/10.1007/978-4-431-55978-8_14
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Amari, Si. (2016). Neyman-Scott Problem: Estimating Function and Semiparametric Statistical Model. In: Information Geometry and Its Applications. Applied Mathematical Sciences, vol 194. Springer, Tokyo. https://doi.org/10.1007/978-4-431-55978-8_9
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DOI: https://doi.org/10.1007/978-4-431-55978-8_9
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Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-55977-1
Online ISBN: 978-4-431-55978-8
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