• 제목/요약/키워드: noncentral chi-square

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Distribution of a Sum of Weighted Noncentral Chi-Square Variables

  • Heo, Sun-Yeong;Chang, Duk-Joon
    • Communications for Statistical Applications and Methods
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    • 제13권2호
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    • pp.429-440
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    • 2006
  • In statistical computing, it is often for researchers to need the distribution of a weighted sum of noncentral chi-square variables. In this case, it is very limited to know its exact distribution. There are many works to contribute to this topic, e.g. Imhof (1961) and Solomon-Stephens (1977). Imhof's method gives good approximation to the true distribution, but it is not easy to apply even though we consider the development of computer technology Solomon-Stephens's three moment chi-square approximation is relatively easy and accurate to apply. However, they skipped many details, and their simulation is limited to a weighed sum of central chi-square random variables. This paper gives details on Solomon-Stephens's method. We also extend their simulation to the weighted sum of non-central chi-square distribution. We evaluated approximated powers for homogeneous test and compared them with the true powers. Solomon-Stephens's method shows very good approximation for the case.

A Sequence of Improvement over the Lindley Type Estimator with the Cases of Unknown Covariance Matrices

  • Kim, Byung-Hwee;Baek, Hoh-Yoo
    • Communications for Statistical Applications and Methods
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    • 제12권2호
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    • pp.463-472
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    • 2005
  • In this paper, the problem of estimating a p-variate (p $\ge$4) normal mean vector is considered in decision-theoretic set up. Using a simple property of the noncentral chi-square distribution, a sequence of estimators dominating the Lindley type estimator with the cases of unknown covariance matrices has been produced and each improved estimator is better than previous one.

Kendall의 Tau에 의한 회귀직선의 평행성에 관한 비모수 검정 (A Nonparametric Test for the Parallelism of Regression Lines Based on Kendall's Tau)

  • Song, Moon-Sup
    • Journal of the Korean Statistical Society
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    • 제7권1호
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    • pp.17-26
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    • 1978
  • For testing $\beta_i=\beta, i=1,...,k$, in the regression model $Y_{ij} = \alpha_i + \beta_ix_{ij} + e_{ij}, j=1,...,n_i$, a simple and robust test based on Kendall's tau is proposed. Its asymptotic distribution is proved to be chi-square under the null hypthesis and noncentral chi-square under an appropriate sequence of alternatives. For the optimal designs, the asymptotic relative efficiency of the proposed procedure with respect to the least squares procedure is the same as that of the Wilcoxon test with respect to the t-test.

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광대역 다중경로 실측채널에서 W-CDMA 수신 신호의 확률분포 모델 (Probability Distribution Model of Received W-CDMA Signals in the Realistic Wideband Multipath Channel)

  • 오동진;이주석;장근영;김철성
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 하계종합학술대회 논문집(1)
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    • pp.197-200
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    • 2000
  • This paper presents a mathematical model of the output of Rake receiver of W-CDMA signals for various outdoor channel environment and different bandwidths. This mathematical model is represented as Rayleigh and noncentral chi distribution with 3 degrees of freedom. Those are obtained from the statistics of numerically generated signals. We employ Chi-square test to show how the mathematical model fits signal statistics, and confirmed that this model is appropriate for representing W-CDMA signals.

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SOME SEQUENCES OF IMPROVEMENT OVER LINDLEY TYPE ESTIMATOR

  • BAEK, HOH-YOO;HAN, KYOU-HWAN
    • 호남수학학술지
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    • 제26권2호
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    • pp.219-236
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    • 2004
  • In this paper, the problem of estimating a p-variate ($p{\geq}4$) normal mean vector is considered in a decision-theoretic setup. Using a simple property of the noncentral chi-square distribution, a sequence of smooth estimators dominating the Lindley type estimator has been produced and each improved estimator is better than previous one.

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An approach to improving the Lindley estimator

  • Park, Tae-Ryoung;Baek, Hoh-Yoo
    • Journal of the Korean Data and Information Science Society
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    • 제22권6호
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    • pp.1251-1256
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    • 2011
  • Consider a p-variate ($p{\geq}4$) normal distribution with mean ${\theta}$ and identity covariance matrix. Using a simple property of noncentral chi square distribution, the generalized Bayes estimators dominating the Lindley estimator under quadratic loss are given based on the methods of Brown, Brewster and Zidek for estimating a normal variance. This result can be extended the cases where covariance matrix is completely unknown or ${\Sigma}={\sigma}^2I$ for an unknown scalar ${\sigma}^2$.

광대역 다중경로 실측채널에서 W-CDMA 수신 신호의 화률 모델 (Probability Models of W-CDMA Signals in Realistic Wideband Multipath Channels)

  • 오동진;이주석;이귀상;김철성
    • 한국통신학회논문지
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    • 제27권4B호
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    • pp.308-315
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    • 2002
  • This paper proposes new probability models for wideband code division multiple access (W-CDMA) signals. The performance of a W-CDMA system is evaluated by calculating the average bit error rate(BER) which is derived from the probability distribution of the W-CDMA receiver output. If a probability model of the receiver output is available, the performance evaluation becomes much simpler and it enables diverse analyses of the system for channel coding and other purposes. In this paper, probability distributions of W-CDMA signals, more specifically those of the receiver output, are represented as Rayleigh and noncentral chi distribution, considering various bandwidths and channel environments. The adequacy of a probability model is verified by chi-square test of 1% significance level. The BER of the system obtained from the simulation results is compared to that obtained from the probability model to demonstrate the usefulness of the proposed models.

An approach to improving the James-Stein estimator shrinking towards projection vectors

  • Park, Tae Ryong;Baek, Hoh Yoo
    • Journal of the Korean Data and Information Science Society
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    • 제25권6호
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    • pp.1549-1555
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    • 2014
  • Consider a p-variate normal distribution ($p-q{\geq}3$, q = rank($P_V$) with a projection matrix $P_V$). Using a simple property of noncentral chi square distribution, the generalized Bayes estimators dominating the James-Stein estimator shrinking towards projection vectors under quadratic loss are given based on the methods of Brown, Brewster and Zidek for estimating a normal variance. This result can be extended the cases where covariance matrix is completely unknown or ${\sum}={\sigma}^2I$ for an unknown scalar ${\sigma}^2$.