On the distribution of the stationary point of significance level for empirical distribution function

被引：0

作者：

Kislitsyn, A. A. ^{[1
]}

Orlov, Yu. N. ^{[1
,2
]}

Moltchanov, D. A. ^{[3
,4
]}

Samuylov, A. K. ^{[3
,4
]}

Chukarin, A. V. ^{[3
]}

Gaidamaka, Yu. V. ^{[3
,5
]}

机构：

[1] RAS, Keldysh Inst Appl Math, Dept Kinet Equat, Moscow, Russia

[2] Peoples Friendship Univ Russia RUDN Univ, Dept Appl Probabil & Informat, Moscow, Russia

[3] Peoples Friendship Univ Russia RUDN Univ, Appl Probabil & Informat Dept, Moscow, Russia

[4] Tampere Univ Technol, Lab Elect & Commun Engn, Tampere, Finland

[5] Fed Res Ctr Comp Sci & Control, Inst Informat Problems, Moscow, Russia

来源：

2018 10TH INTERNATIONAL CONGRESS ON ULTRA MODERN TELECOMMUNICATIONS AND CONTROL SYSTEMS AND WORKSHOPS (ICUMT 2018): EMERGING TECHNOLOGIES FOR CONNECTED SOCIETY | 2018年

关键词：

D2D communications; non-stationary distribution function; significance level; stationary point; Chernoff equivalence;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We consider empirical distribution functions of nonstationary time-series, depending on set length. The local selfconsistent significance level is introduced. The class of timeseries, for which the distribution function of significance level is stationary, is considered. For example, the signal-to-interference ratio for random walking subscribers in D2D model of wireless connection belongs to this class of random processes. We introduce also the so-called Chernoff equivalence of the self-consistent significance level and derive the formula of averaging levels for various sets.

引用

页数：5

共 50 条

[31] GENERALIZED EQUATIONS FOR THE OBJECTIVE EMPIRICAL DISTRIBUTION FUNCTION
SCHREIBER, F
[J]. AEU-ARCHIV FUR ELEKTRONIK UND UBERTRAGUNGSTECHNIK-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, 1982, 36 (04): : 168 - 172
[32] MINIMAXITY OF THE EMPIRICAL DISTRIBUTION FUNCTION IN INVARIANT ESTIMATION
YU, QQ
CHOW, MS
[J]. ANNALS OF STATISTICS, 1991, 19 (02): : 935 - 951
[33] Bootstrapping the empirical distribution function of a spatial process
Zhu J.
Lahiri S.N.
[J]. Statistical Inference for Stochastic Processes, 2007, 10 (2) : 107 - 145
[34] A test for normality based on the empirical distribution function
Torabi, Hamzeh
Montazeri, Narges H.
Grane, Aurea
[J]. SORT-STATISTICS AND OPERATIONS RESEARCH TRANSACTIONS, 2016, 40 (01) : 55 - 87
[35] The least concave majorant of the empirical distribution function
Carolan, CA
[J]. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 2002, 30 (02): : 317 - 328
[36] Uniform convergence of the empirical spectral distribution function
Mikosch, T
Norvaisa, R
[J]. STOCHASTIC PROCESSES AND THEIR APPLICATIONS, 1997, 70 (01) : 85 - 114
[37] A test for normality based on the empirical distribution function
[J]. 1600, Institut d'Estadistica de Catalunya (40):
[38] Empirical distribution function in an experiment with binomial randomization
Shipilov, OI
[J]. THEORY OF PROBABILITY AND ITS APPLICATIONS, 1997, 41 (02) : 307 - 317
[39] NON-NEGATIVE JUMP POINTS OF AN EMPIRICAL DISTRIBUTION FUNCTION RELATIVE TO A THEORETICAL DISTRIBUTION FUNCTION
PING, C
[J]. CHINESE MATHEMATICS, 1967, 9 (01): : 31 - &
[40] Stationary Distribution Function Estimation for Ergodic Diffusion Process
Ilia Negri
[J]. Statistical Inference for Stochastic Processes, 1998, 1 (1) : 61 - 84

← 1 2 3 4 5 →