• Communications for Statistical Applications and Methods
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• 제5권2호
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• pp.531-538
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• 1998

This paper first examines the skewness of Wishart distribution, using Tracy and Sultan(1993)'s results. Second, it investigates the variance-covariance matrix of random matrix $S_Y=YY'$ which has a non-central Wishart distribution. Third, it proposes the exact form of the third moment of the random matrix with non-central Wishart distribution.

• Journal of the Korean Statistical Society
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• 제21권2호
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• pp.127-137
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• 1992

In this paper we investigate scaling limits for associated random measures satisfying some moment conditions. No stationarity is required. Our results imply an improvement of a central limit theorem of Cox and Grimmett to associated random measure and an extension to the nonstationary case of scaling limits of Burton and Waymire. Also we prove an invariance principle for associated random measures which is an extension of the Birkel's invariance principle for associated process.

• Journal of the Korean Statistical Society
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• 제30권1호
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• pp.115-125
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• 2001

We consider the threshold autoregressive moving average(TARMA) process and find a sufficient condition for strict stationarity of the proces. Given region for stationarity of TARMA(p,q) model is the same as that of TAR(p) model given by Chan and Tong(1985), which shows that the moving average part of TARMA(p,q) process does not affect the stationarity of the process. We find also a sufficient condition for the existence of kth moments(k$\geq$1) of the process with respect to the stationary distribution.

• Journal of the Korean Statistical Society
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• 제24권1호
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• pp.183-195
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• 1995

For a distribution on the unit sphere, the set of eigenvectors of the second moment matrix is a conventional measure of orientation. Asymptotic confidence cones for eigenvector under the parametric assumptions for the underlying distributions and nonparametric confidence cones for eigenvector based on bootstrapping were proposed. In this paper, to reduce the level error of confidence cones for eigenvector, double bootstrap confidence cones based on prepivoting are considered, and the consistency of this method is discussed. We compare the perfomances of double bootstrap method with the others by Monte Carlo simulations.

• Journal of the Korean Statistical Society
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• 제24권1호
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• pp.233-242
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• 1995

In this paper we will prove the existence and uniqueness of the smoothest density with prescribed moments. The space of functions considered is the Sobolev space $W^2_m[0,1]$ and the target functional to be minimized is the seminorm $$\mid$$\mid$f^{(m)}$\mid$$\mid$_{L^2}$, which measures the roughness of the function f.

• Journal of the Korean Statistical Society
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• 제23권1호
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• pp.39-51
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• 1994

Some exponential moment inequalities for sub-gaussian random variables are studied in this paper. These inequalities are used to obtain laws of large numbers for random variable and random elements in $L^1(R)$.

• Communications for Statistical Applications and Methods
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• 제12권1호
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• pp.253-264
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• 2005

Hader and Park(l978) suggested the concept of slope-rotatability in axial directions for second order response surface designs. In this paper, the moment conditions for slope-rotatability in axial directions are shown and the measures for evaluating slope-rotatability in axial directions are proposed.

• Journal of the Korean Statistical Society
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• 제25권4호
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• pp.557-566
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• 1996

The aim of this paper is to find a suitable design which minimizes the expected discrepancy: in fitting a first order model fearing quadratic terms as bias where there are more than two correlated responses. Kim and Draper(1994) discussed about choosing a design for straight line fits to two correlated responses The general case with r responses is examined here and the result is applied to a specific case to help understandings.

• Journal of the Korean Statistical Society
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• 제36권3호
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• pp.357-365
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• 2007

In this paper we present characterizations of the Pareto, Lomax, exponential and beta models by some properties of their $r^{th}$ partial moment defined as ${\alpha}_r(t)=E[(X-t)^+]^r$, where $(X-t)^+ = max(X-t,0)$. Given the partial moments at a few truncation points, these results enable us to calculate the moments at many other points.

• Communications for Statistical Applications and Methods
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• 제16권5호
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• pp.859-870
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• 2009

We obtain a skewed double Weibull distribution by a double Weibull distribution, and evaluate its coefficient of skewness. And we obtain the approximate maximum likelihood estimator(AML) and moment estimator of skew parameter in the skewed double Weibull distribution, and hence compare simulated mean squared errors(MSE) of those estimators. We compare simulated MSE of two proposed reliability estimators in two independent skewed double Weibull distributions each with different skew parameters. Finally we introduce a skewed double Weibull distribution generated by a uniform kernel.