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On some statistical properties of the “Book Stack” transformation. / Bzikadze, A. V. ; Nekrutkin, V. V. .
в: Vestnik St. Petersburg University: Mathematics, Том 49, 2016, стр. 305-312.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
}
TY - JOUR
T1 - On some statistical properties of the “Book Stack” transformation
AU - Bzikadze, A. V.
AU - Nekrutkin, V. V.
N1 - Bzikadze, A.V., Nekrutkin, V.V. On some statistical properties of the “Book Stack” transformation. Vestnik St.Petersb. Univ.Math. 49, 305–312 (2016). https://doi.org/10.3103/S106345411604004X
PY - 2016
Y1 - 2016
N2 - This paper is devoted to studying the statistical properties of the “Book Stack” transformation proposed by B.Ya. Ryabko (Probl. Inf. Transm., 1980, vol. 16, no. 4) as a data compression method. The same transformation has been used by Ryabko and A.I. Pestunov (Probl. Inf. Transm., 2004, vol. 40, no. 1) to construct the similarly named statistical test. This test is designed for the verification of the null hypothesis that an available input i.i.d. sample corresponds to a discrete uniform distribution with a known support. They propose to verify this hypothesis for a new sample obtained via the Book Stack transformation instead of the input sample. This gives rise to the natural problem of comparing the results given by the same statistical test in the application to input and output samples. If the null hypothesis is true, these procedures prove to be equivalent; however, this is actually not the case anymore when there are some violations of this hypothesis. The results of comparing the criteria surely depend on the class of the alternatives considered. This paper deals with the natural alternative consisting of the fact that the initial replicated sample corresponds to a discrete, albeit, nonuniform, distribution with a fixed support. It has been demonstrated that some standard criteria for the verification of the null hypothesis prove to be more powerful for an input sample in comparison with a transformed sample. In particular, this takes place for the likelihood ratio criterion and (with some formal constraints) the χ2-criterion.
AB - This paper is devoted to studying the statistical properties of the “Book Stack” transformation proposed by B.Ya. Ryabko (Probl. Inf. Transm., 1980, vol. 16, no. 4) as a data compression method. The same transformation has been used by Ryabko and A.I. Pestunov (Probl. Inf. Transm., 2004, vol. 40, no. 1) to construct the similarly named statistical test. This test is designed for the verification of the null hypothesis that an available input i.i.d. sample corresponds to a discrete uniform distribution with a known support. They propose to verify this hypothesis for a new sample obtained via the Book Stack transformation instead of the input sample. This gives rise to the natural problem of comparing the results given by the same statistical test in the application to input and output samples. If the null hypothesis is true, these procedures prove to be equivalent; however, this is actually not the case anymore when there are some violations of this hypothesis. The results of comparing the criteria surely depend on the class of the alternatives considered. This paper deals with the natural alternative consisting of the fact that the initial replicated sample corresponds to a discrete, albeit, nonuniform, distribution with a fixed support. It has been demonstrated that some standard criteria for the verification of the null hypothesis prove to be more powerful for an input sample in comparison with a transformed sample. In particular, this takes place for the likelihood ratio criterion and (with some formal constraints) the χ2-criterion.
KW - data compression
KW - Book Stack transformation
KW - discrete uniform distribution
KW - statistical hypothesis
UR - https://link.springer.com/article/10.3103/S106345411604004X
M3 - Article
VL - 49
SP - 305
EP - 312
JO - Vestnik St. Petersburg University: Mathematics
JF - Vestnik St. Petersburg University: Mathematics
SN - 1063-4541
ER -
ID: 15492185