• 제목/요약/키워드: rate of statistical convergence

검색결과 139건 처리시간 0.024초

STATISTICAL CONVERGENCE FOR GENERAL BETA OPERATORS

  • Deo, Naokant;Ozarslan, Mehmet Ali;Bhardwaj, Neha
    • Korean Journal of Mathematics
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    • 제22권4호
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    • pp.671-681
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    • 2014
  • In this paper, we consider general Beta operators, which is a general sequence of integral type operators including Beta function. We study the King type Beta operators which preserves the third test function $x^2$. We obtain some approximation properties, which include rate of convergence and statistical convergence. Finally, we show how to reach best estimation by these operators.

Density by Moduli and Korovkin Type Approximation Theorem of Boyanov and Veselinov

  • Bhardwaj, Vinod K.;Dhawan, Shweta
    • Kyungpook Mathematical Journal
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    • 제58권4호
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    • pp.733-746
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    • 2018
  • The concept of f-statistical convergence which is, in fact, a generalization of statistical convergence, has been introduced recently by Aizpuru et al. (Quaest. Math. 37: 525-530, 2014). The main object of this paper is to prove an f-statistical analog of the classical Korovkin type approximation theorem of Boyanov and Veselinov. It is shown that the f-statistical analog is intermediate between the classical theorem and its statistical analog. As an application, we estimate the rate of f-statistical convergence of the sequence of positive linear operators defined from $C^*[0,{\infty})$ into itself.

Optimal Convergence Rate of Empirical Bayes Tests for Uniform Distributions

  • Liang, Ta-Chen
    • Journal of the Korean Statistical Society
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    • 제31권1호
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    • pp.33-43
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    • 2002
  • The empirical Bayes linear loss two-action problem is studied. An empirical Bayes test $\delta$$_{n}$ $^{*}$ is proposed. It is shown that $\delta$$_{n}$ $^{*}$ is asymptotically optimal in the sense that its regret converges to zero at a rate $n^{-1}$ over a class of priors and the rate $n^{-1}$ is the optimal rate of convergence of empirical Bayes tests.sts.

Rate of Convergence of Empirical Distributions and Quantiles in Linear Processes with Applications to Trimmed Mean

  • Lee, Sangyeol
    • Journal of the Korean Statistical Society
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    • 제28권4호
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    • pp.435-441
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    • 1999
  • A 'convergence in probability' rate of the empirical distributions and quantiles of linear processes is obtained. As an application of the limit theorems, a trimmed mean for the location of the linear process is considered. It is shown that the trimmed mean is asymptotically normal. A consistent estimator for the asymptotic variance of the trimmed mean is provided.

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통계처리를 활용한 터널 내공변위의 분석에 관한 연구 (Estimation of Tunnel Convergence Using Statistical Analysis)

  • 김종우
    • 터널과지하공간
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    • 제13권2호
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    • pp.108-116
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    • 2003
  • 백악기 경상계 안산암과 불국사 화강암류가 주로 분포하는 지반에서 시공된 터널의 내공변위 계측자료를 분석하였다. 터널 주변 암반을 RMR법에 의한 다섯 가지 암반등급으로 구분하고 각 등급에 포함된 계측자료들을 통계처리하여 암반등급별 내공변위의 회귀분석을 실시하였다. 연구 결과. 로그함수보다는 지수함수의 상관계수 가 더 크며, 연약한 암반등급일수록 내공변위의 크기와 표준편차가 크게 나타났다. 또한, 최종내공변위에 대한 최대변위속도 및 초기내공변위의 관계를 도출하였으며, 이 중에서 최종내공변위와 최대변위속도의 상관계수는 0.87로 나타나 이들은 비교적 높은 상관성을 가지는 것으로 확인되었다

ON STATISTICAL APPROXIMATION PROPERTIES OF MODIFIED q-BERNSTEIN-SCHURER OPERATORS

  • Ren, Mei-Ying;Zeng, Xiao-Ming
    • 대한수학회보
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    • 제50권4호
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    • pp.1145-1156
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    • 2013
  • In this paper, a kind of modified $q$-Bernstein-Schurer operators is introduced. The Korovkin type statistical approximation property of these operators is investigated. Then the rates of statistical convergence of these operators are also studied by means of modulus of continuity and the help of functions of the Lipschitz class. Furthermore, a Voronovskaja type result for these operators is given.

On the Almost Certain Rate of Convergence of Series of Independent Random Variables

  • Nam, Eun-Woo;Andrew Rosalsky
    • Journal of the Korean Statistical Society
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    • 제24권1호
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    • pp.91-109
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    • 1995
  • The rate of convergence to a random variable S for an almost certainly convergent series $S_n = \sum^n_{j=1} X_j$ of independent random variables is studied in this paper. More specifically, when $S_n$ converges to S almost certainly, the tail series $T_n = \sum^{\infty}_{j=n} X_j$ is a well-defined sequence of random variable with $T_n \to 0$ a.c. Various sets of conditions are provided so that for a given numerical sequence $0 < b_n = o(1)$, the tail series strong law of large numbers $b^{-1}_n T_n \to 0$ a.c. holds. Moreover, these results are specialized to the case of the weighted i.i.d. random varialbes. Finally, example are provided and an open problem is posed.

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Kernel Density Estimation in the L$^{\infty}$ Norm under Dependence

  • Kim, Tae-Yoon
    • Journal of the Korean Statistical Society
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    • 제27권2호
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    • pp.153-163
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    • 1998
  • We investigate density estimation problem in the L$^{\infty}$ norm and show that the iii optimal minimax rates are achieved for smooth classes of weakly dependent stationary sequences. Our results are then applied to give uniform convergence rates for various problems including the Gibbs sampler.

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BERRY-ESSEEN BOUND FOR MLE FOR LINEAR STOCHASTIC DIFFERENTIAL EQUATIONS DRIVEN BY FRACTIONAL BROWNIAN MOTION

  • RAO B.L.S. PRAKASA
    • Journal of the Korean Statistical Society
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    • 제34권4호
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    • pp.281-295
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    • 2005
  • We investigate the rate of convergence of the distribution of the maximum likelihood estimator (MLE) of an unknown parameter in the drift coefficient of a stochastic process described by a linear stochastic differential equation driven by a fractional Brownian motion (fBm). As a special case, we obtain the rate of convergence for the case of the fractional Ornstein- Uhlenbeck type process studied recently by Kleptsyna and Le Breton (2002).

Empirical Bayes Test for the Exponential Parameter with Censored Data

  • Wang, Lichun
    • Communications for Statistical Applications and Methods
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    • 제15권2호
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    • pp.213-228
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    • 2008
  • Using a linear loss function, this paper considers the one-sided testing problem for the exponential distribution via the empirical Bayes(EB) approach. Based on right censored data, we propose an EB test for the exponential parameter and obtain its convergence rate and asymptotic optimality, firstly, under the condition that the censoring distribution is known and secondly, that it is unknown.