On uniform consistency of nonparametric tests
Zapiski Nauchnykh Seminarov POMI, Probability and statistics. Part 35, Tome 526 (2023), pp. 78-89 Cet article a éte moissonné depuis la source Math-Net.Ru

Voir la notice du chapitre de livre

For problem of hypothesis testing on a density we explore condition of existence of uniformly consistent tests. Hypothesis is simple. Sets of alternatives is convex sets in $\mathbb{L}_p$, $p>1$, with deleted balls. Hypothesis is center of balls. We show that, there is sequence of radii of the balls tending to zero as sample size increases such that the sets of alternatives are uniformly consistent, if and only if convex set is compact. Similar results are established for problem of hypothesis testing on a density, for signal detection in Gaussian white noise, for linear ill-posed problems with random Gaussian noise and so on.
@article{ZNSL_2023_526_a4,
     author = {M. S. Ermakov},
     title = {On uniform consistency of nonparametric tests},
     journal = {Zapiski Nauchnykh Seminarov POMI},
     pages = {78--89},
     year = {2023},
     volume = {526},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/ZNSL_2023_526_a4/}
}
TY  - JOUR
AU  - M. S. Ermakov
TI  - On uniform consistency of nonparametric tests
JO  - Zapiski Nauchnykh Seminarov POMI
PY  - 2023
SP  - 78
EP  - 89
VL  - 526
UR  - http://geodesic.mathdoc.fr/item/ZNSL_2023_526_a4/
LA  - ru
ID  - ZNSL_2023_526_a4
ER  - 
%0 Journal Article
%A M. S. Ermakov
%T On uniform consistency of nonparametric tests
%J Zapiski Nauchnykh Seminarov POMI
%D 2023
%P 78-89
%V 526
%U http://geodesic.mathdoc.fr/item/ZNSL_2023_526_a4/
%G ru
%F ZNSL_2023_526_a4
M. S. Ermakov. On uniform consistency of nonparametric tests. Zapiski Nauchnykh Seminarov POMI, Probability and statistics. Part 35, Tome 526 (2023), pp. 78-89. http://geodesic.mathdoc.fr/item/ZNSL_2023_526_a4/

[1] L. Birge, “Robust tests for model selection”, IMS Collections, 9 (2012), 47–64 | MR

[2] M. V. Burnashev, “On the minimax solution of inaccurately known signal in a white Gaussian noise. Background”, Theory Probab. Appl., 24 (1979), 107–119 | DOI | MR | Zbl

[3] A. Dembo, Y. Peres, “A topological criterion for hypothesis testing”, Ann. Statist., 22 (1994), 106–117 | DOI | MR | Zbl

[4] N. Dunford, J. T. Schwartz, Linear operators, Interscience Publishers, NY, 1958 | MR | Zbl

[5] H. Engl, M. Hanke, A. Neubauer, Regularization of Inverse Problems, Kluwer, 1996 | MR | Zbl

[6] M. S. Ermakov, “On consistent hypothesis testing”, J. Math. Sci., 225 (2017), 751–769 | DOI | MR | Zbl

[7] M. S. Ermakov, “Minimax nonparametric estimation on maxisets”, J. Math. Sci., 244 (2020), 779–788 | DOI | MR | Zbl

[8] M. S. Ermakov, “On asymptotically minimax nonparametric detection of signal in Gaussian white noise”, J. Math. Sci., 251 (2020), 78–87 | DOI | MR | Zbl

[9] M. S. Ermakov, “On uniform consistency of nonparametric tests I”, J. Math. Sci., 258 (2021), 802–837 | DOI | MR | Zbl

[10] P. Gänssler, “Compactness and sequential compactness on the space of measures”, Z. Wahrsch. Verw. Geb., 17 (1971), 124–146 | DOI | MR

[11] I. A. Ibragimov, R. Z. Khasminskii, “On the estimation of infinitely dimensional parameter in Gaussian white noise”, Dokl. AN USSR, 236 (1977), 1053–1055 | MR | Zbl

[12] W. Hoeffding, J. Wolfowitz, “Distinguishability of sets of distributions”, Ann. Math. Statist., 29 (1958), 700–718 | DOI | MR | Zbl

[13] Yu. I. Ingster, “Asymptotically minimax hypothesis testing for nonparametric alternatives. I, II, III”, Math. Methods Statist., 2 (1993), 85–114 ; 171–189 ; 249–268 | MR | Zbl | MR | Zbl | MR | Zbl

[14] Yu. I. Ingster, Yu. A. Kutoyants, “Nonparametric hypothesis testing for intensity of the Poisson process”, Math. Methods Statist., 16 (2007), 218–246 | MR

[15] Yu. I. Ingster, I. A. Suslina, Nonparametric Goodness-of-fit Testing under Gaussian Models, Lect. Notes Statist., 169, Springer, NY, 2002 | MR

[16] A. Janssen, “Global power function of goodness of fit tests”, Ann. Statist., 28 (2020), 239–253 | MR

[17] G. Kerkyacharian, D. Picard, “Density estimation by kernel and wavelets methods: optimality of Besov spaces”, Statist. Probab. Lett., 18 (1993), 327–336 | DOI | MR | Zbl

[18] C. Kraft, “Some conditions for consistency and uniform consistency of statistical procedures”, Univ. Californ. Publ. Statist., 2 (1955), 125–142 | MR | Zbl

[19] V. Krotov, “Criteria for compactness in $\mathbb{L}_p$-spaces, $p>0$”, Russian Acad. Sci. Sbornik Math., 203:7 (2012), 1045–1064 | DOI | MR | Zbl

[20] L. Le Cam, “Convergence of estimates under dimensionality restrictions”, Ann. Statist., 1 (1973), 38–53 | MR | Zbl

[21] L. Le Cam, L. Schwartz, “A necessary and sufficient conditions for the existence of consistent estimates”, Ann. Math. Statist., 31 (1960), 140–150 | DOI | MR | Zbl

[22] J. Pfanzagl, “On the existence of consistent estimates and tests”, Z. Wahrsch. Verw. Geb., 10 (1968), 43–62 | DOI | MR | Zbl

[23] V. Rivoirard, “Maxisets for linear procedures”, Statist. Probab. Lett., 67 (2004), 267–275 | DOI | MR | Zbl

[24] Y. Wei, M. J. Wainwright, “The local geometry of testing in ellipses: tight control via localized Kolmogorov widths”, IEEE Trans. Inform. Theory, 66:8 (2020), 5110–5129 | DOI | MR | Zbl