Identifying the Closest Symmetric Distribution or Density Function
Schuster, Eugene F.
Ann. Statist., Tome 15 (1987) no. 1, p. 865-874 / Harvested from Project Euclid
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The problem addressed is that of finding the "closest" symmetric distribution (density) to a given theoretical or empirical distribution (density) function. Measures of "closeness" considered include: weighted sup norm, weighted $L_p$ norm and Hellinger distance. Explicit formulas are given for the closest symmetric distribution function to the empirical distribution function in both sup norm and integrated square error.
Publié le : 1987-06-14
Classification:  Empirical distribution function,  symmetrical distribution,  symmetrical density,  closest symmetrical distribution,  symmetrical bootstrap,  minimum distance,  62E99,  62G99 
@article{1176350380,
     author = {Schuster, Eugene F.},
     title = {Identifying the Closest Symmetric Distribution or Density Function},
     journal = {Ann. Statist.},
     volume = {15},
     number = {1},
     year = {1987},
     pages = { 865-874},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176350380}
}

Schuster, Eugene F. Identifying the Closest Symmetric Distribution or Density Function. Ann. Statist., Tome 15 (1987) no. 1, pp.  865-874. http://gdmltest.u-ga.fr/item/1176350380/