Asymptotic Theory of Sequential Estimation: Differential Geometrical Approach
Okamoto, Ichi ; Amari, Shun-Ichi ; Takeuchi, Kei
Ann. Statist., Tome 19 (1991) no. 1, p. 961-981 / Harvested from Project Euclid
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Sequential estimation continues observations until the observed sample satisfies a prescribed criterion. Its properties are superior on the average to those of nonsequential estimation in which the number of observations is fixed a priori. A higher-order asymptotic theory of sequential estimation is given in the framework of geometry of multidimensional curved exponential families. This gives a design principle of the second-order efficient sequential estimation procedure. It is also shown that a sequential estimation can be designed to have a covariance stabilizing effect at the same time.
Publié le : 1991-06-14
Classification:  Asymptotic theory,  conformal transformation,  covariance stabilization,  differential geometry,  higher-order asymptotics,  sequential estimation,  statistical curvature,  stopping rule,  62F10,  62F12 
@article{1176348131,
     author = {Okamoto, Ichi and Amari, Shun-Ichi and Takeuchi, Kei},
     title = {Asymptotic Theory of Sequential Estimation: Differential Geometrical Approach},
     journal = {Ann. Statist.},
     volume = {19},
     number = {1},
     year = {1991},
     pages = { 961-981},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176348131}
}

Okamoto, Ichi; Amari, Shun-Ichi; Takeuchi, Kei. Asymptotic Theory of Sequential Estimation: Differential Geometrical Approach. Ann. Statist., Tome 19 (1991) no. 1, pp.  961-981. http://gdmltest.u-ga.fr/item/1176348131/