• 제목/요약/키워드: Order statistics

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On the Exponentiated Generalized Modified Weibull Distribution

  • Aryal, Gokarna;Elbatal, Ibrahim
    • Communications for Statistical Applications and Methods
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    • 제22권4호
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    • pp.333-348
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    • 2015
  • In this paper, we study a generalization of the modified Weibull distribution. The generalization follows the recent work of Cordeiro et al. (2013) and is based on a class of exponentiated generalized distributions that can be interpreted as a double construction of Lehmann. We introduce a class of exponentiated generalized modified Weibull (EGMW) distribution and provide a list of some well-known distributions embedded within the proposed distribution. We derive some mathematical properties of this class that include ordinary moments, generating function and order statistics. We propose a maximum likelihood method to estimate model parameters and provide simulation results to assess the model performance. Real data is used to illustrate the usefulness of the proposed distribution for modeling reliability data.

BACKPROPAGATION BASED ON THE CONJUGATE GRADIENT METHOD WITH THE LINEAR SEARCH BY ORDER STATISTICS AND GOLDEN SECTION

  • Choe, Sang-Woong;Lee, Jin-Choon
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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    • pp.107-112
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    • 1998
  • In this paper, we propose a new paradigm (NEW_BP) to be capable of overcoming limitations of the traditional backpropagation(OLD_BP). NEW_BP is based on the method of conjugate gradients with the normalized direction vectors and computes step size through the linear search which may be characterized by order statistics and golden section. Simulation results showed that NEW_BP was definitely superior to both the stochastic OLD_BP and the deterministic OLD_BP in terms of accuracy and rate of convergence and might sumount the problem of local minima. Furthermore, they confirmed us that stagnant phenomenon of training in OLD_BP resulted from the limitations of its algorithm in itself and that unessential approaches would never cured it of this phenomenon.

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The Cusum of Squares Test for Variance Changes in Infinite Order Autoregressive Models

  • Park, Siyun;Lee, Sangyeol;Jongwoo Jeon
    • Journal of the Korean Statistical Society
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    • 제29권3호
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    • pp.351-360
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    • 2000
  • This paper considers the problem of testing a variance change in infinite order autoregressive models. A cusum of squares test based on the residuals from an AR(q) model is constructed analogous to Inclan and Tiao (1994)'s test statistic, where q is a sequence of positive integers diverging to $\infty$. It is shown that under regularity conditions the limiting distribution of the test statistic is the sup of a standard Brownian bridge. Simulation results are given to illustrate the performance of the test.

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채널의 1차 2차 통계적 특성이 큐의 성능에 미치는 영향 (Effect of First and Second Order Channel Statistics on Queueing Performance)

  • 김영용
    • 제어로봇시스템학회논문지
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    • 제8권4호
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    • pp.288-291
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    • 2002
  • We characterize multipath fading channel dynamics at the packet level and analyze the corresponding data queueing performance in various environments. We identify the similarity between wire-line queueing analysis and wireless network per-formance analysis. The second order channel statistics, i.e. channel power spectrum, is fecund to play an important role in the modeling of multipath fading channels. However, it is identified that the first order statistics, i.e. channel CDF also has significant impact on queueing performance. We use a special Markov chain, so-called CMPP, throughout this paper.

시간-주파수 마스킹과 고차 신호 통계를 이용한 음향 반향신호 제거 (Acoustic Echo Cancellation using Time-Frequency Masking and Higher-order Statistics)

  • 김경재;남상원
    • 전기학회논문지
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    • 제56권3호
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    • pp.629-631
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    • 2007
  • In hands-free full-duplex communication systems, acoustic signals picked up by the microphones can be mixed with echo signals as well as noises, which may result in poor performance of the corresponding communication system. Also, the system performance may decrease further if the reverberation occurs since it is harder to estimate the impulse response of the demixing system. For blind source separation (BSS) in such cases, a time-frequency masking approach can be employed to separate undesired echo signals and noises, but, permutation ambiguities also should be solved for the echo cancellation. In this paper, we propose a new acoustic echo cancellation (AEC) approach utilizing the time-frequency masking and higher-order statistics, whereby a desired signal selection, based on coherence and third-order statistics (i.e., kurtosis), is introduced along with output signal normalization. Simulation results demonstrate that the proposed approach yields better echo and noise cancellation performances than the conventional AEC approaches.

Graphical Estimation of the Parameters of the Stable Laws

  • Paulson, Albert-S.;Won, Hyung-Gyoo
    • Management Science and Financial Engineering
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    • 제2권1호
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    • pp.103-122
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    • 1996
  • This paper presents an easily used graphical procedure for simultaneous estimation of the index, skewness, scale, and location parameters of the stable laws. First, the index $\alpha$ and skewness $\beta$ are estimated through the joint use of a tail length statistic $\widetilde{K_t}$ and a skewness statistic $\widetilde{K_s}$, both of which are functions of order statistics. Next, the function of order statistics needed for estimation of scale $\sigma$ and location $\mu$ are determined from a nomogram indexed on the estimates of $\alpha$ and $\beta$. Some applications and examples are provided.

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2차 통계량을 이용한 배열 안테나의 도래 방향 추정 (DOA Estimation of Arrays Antenna using Second Order Statistics)

  • 변건식;장은영
    • 한국정보통신학회논문지
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    • 제9권3호
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    • pp.522-527
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    • 2005
  • 이동 통신단말의 급속한 보급에 따라 고품질이며 대용량인 정보의 전송이 요구된다. 또한 고속 전송 시 발생하는 다중로 페이딩을 해결하기 위해 적응 배열 안테나의 연구가 활발히 진행되고 있으며, 그 중 DOA(Direction of Arrival) 추정은 적응배열 안테나의 중요한 부분이다. 본 논문에서는, 2차 통계량을 이용한 시공간 블라인드 시스템 식별을 제안하고, 블라인드 시공간 적응 배열 안테나를 이용하여 제안 방법의 효율성을 입증한다.

A NOTE ON THE CONVERGENCE OF TRIVARIATE EXTREME ORDER STATISTICS AND EXTENSION

  • BARAKAT H. M.;NIGM E. M.;ASKAR M. M.
    • Journal of applied mathematics & informatics
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    • 제18권1_2호
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    • pp.247-259
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    • 2005
  • Necessary and sufficient conditions, under which there exists (at least) a sequence of vectors of real numbers for which the distribution function (d.f.) of any vector of extreme order statistics converges to a non-degenerate limit, are derived. The interesting thing is that these conditions solely depend on the univariate marginals. Moreover, the limit splits into the product of the limit univariate marginals if all the bivariate marginals of the trivariate d.f., from which the sample is drawn, is of negative quadrant dependent random variables (r.v.'s). Finally, all these results are stated for the multivariate extremes with arbitrary dimensions.

Robust inference with order constraint in microarray study

  • Kang, Joonsung
    • Communications for Statistical Applications and Methods
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    • 제25권5호
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    • pp.559-568
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    • 2018
  • Gene classification can involve complex order-restricted inference. Examining gene expression pattern across groups with order-restriction makes standard statistical inference ineffective and thus, requires different methods. For this problem, Roy's union-intersection principle has some merit. The M-estimator adjusting for outlier arrays in a microarray study produces a robust test statistic with distribution-insensitive clustering of genes. The M-estimator in conjunction with a union-intersection principle provides a nonstandard robust procedure. By exact permutation distribution theory, a conditionally distribution-free test based on the proposed test statistic generates corresponding p-values in a small sample size setup. We apply a false discovery rate (FDR) as a multiple testing procedure to p-values in simulated data and real microarray data. FDR procedure for proposed test statistics controls the FDR at all levels of ${\alpha}$ and ${\pi}_0$ (the proportion of true null); however, the FDR procedure for test statistics based upon normal theory (ANOVA) fails to control FDR.

Analysis of the Generalized Order Statistics Constant False Alarm Rate Detector

  • Kim, Chang-Joo;Lee, Hwang-Soo
    • ETRI Journal
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    • 제16권1호
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    • pp.17-34
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    • 1994
  • In this paper, we present an architecture of the constant false alarm rate (CFAR) detector called the generalized order statistics (GOS) CFAR detector, which covers various order statistics (OS) and cell-averaging (CA) CFAR detectors as special cases. For the proposed GOS CFAR detector, we obtain unified formulas for the false alarm and detection probabilities. By properly choosing coefficients of the GOS CFAR detector, one can utilize any combination of ordered samples to estimate the background noise level. Thus, if we use a reference window of size N, we can realize $(2^N-1)$ kinds of CFAR processors and obtain their performances from the unified formulas. Some examples are the CA, the OS, the censored mean level, and the trimmed mean CFAR detectors. As an application of the GOS CFAR detector to multiple target detection, we propose an algorithm called the adaptive mean level detector, which censors adaptively the interfering target returns in a reference window.

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