• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.347-349
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• 1995

In this paper a central limit theorem on $L^P(R)$ for $1{\leq}p<{\infty}$ is obtained with an example when ${X_n}$ is a sequence of independent, identically distributed random variables on $L^P(R)$.

• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.291-296
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• 2000

Petrov(1996) examined the connection between general moment conditions and the applicability of the strong law lf large numbers to a sequence of pairwise independnt and identically distributed random variables. In this note wee generalize Theorem 1 of Petrov(1996) and also show that still holds under assumption of pairwise negative quadrant dependence(NQD).

• Journal of the Korean Statistical Society
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• v.34 no.1
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• pp.11-20
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• 2005

The distributional properties of R = X/(X + Y) and related estimation procedures are derived when X and Y are independent and identically distributed according to the Weibull or Levy distribution. The work is of interest in biological and physical sciences, econometrics, engineering and ranking and selection.

• Journal of the Korean Statistical Society
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• v.27 no.3
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• pp.349-358
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• 1998

Consider the AR(1) model $X_{t}$=$\beta$ $X_{t-1}$+$\varepsilon$$_{t}$ where $\beta$ < 1 is an unknown parameter to be estimated and {$\varepsilon$$_{t}$} denotes the independent and identically distributed error terms with unknown common distribution function F. In this paper, a strong representation for the least absolute deviation (LAD) estimate of $\beta$ in AR(1) models is obtained under some mild conditions on F. on F.F.

• Journal of the Korean Statistical Society
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• v.36 no.4
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• pp.579-593
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• 2007

The distributional properties of Pr(Y

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.65-66
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• 2007

In this paper, a bit error rate (BER) study is presented for decode-and-forward (DF) relaying for user cooperation in independent and identically distributed Rayleigh fading channels.

• Journal of Korean Institute of Industrial Engineers
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• v.4 no.1
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• pp.29-32
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• 1978

We obtain the minimum variance unbiased estimate of system reliability when a system consists of n components whose life times are assumed to be independent and identically distributed either negative exponential or geometric random variables. For the case of a negative exponential life time, we obtain the minimum variance unbiased estimate of the probability density function of the i-th order statistic.

• Journal of the Korean Statistical Society
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• v.32 no.1
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• pp.21-24
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• 2003

In the recent papers by Harris and Park (1994) and by Hui and Park (2000), a family of lattice distributions derived from a sum of independent identically distributed random variables is examined. In this paper we generalize a result of Hui and Park (2000) on lattice distributions on the torus using the Poisson summation formula.

• Journal of the Korean Statistical Society
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• v.32 no.3
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• pp.289-298
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• 2003

We consider the estimation problem for the scale parameter of the Rayleigh distribution using weighted balanced loss function (WBLF) which reflects both goodness of fit and precision. Under WBLF, we obtain the optimal estimator which creates a kind of balance between Bayesian and non-Bayesian estimation. We also deal with the estimation of R ＝ P(Y < X) when Y and X are two independent but not identically distributed Rayleigh distribution under squared error loss function.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.25
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• pp.75-82
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• 1992

Standard acceptance sampling plans models the production pricess as a sequence of independent identically distributed Beruoulli random variables. However, the quality of items sampled sequentially from an ongoing production process of ten exhibits statistical dependency that is not accounted for in standard acceptance sampling plans. In this paper, a dependent production process is modelled as an ARMA process and as a two-state Markov chain. A simulation study of each is performed. A comparison of the probability of acceptance is done for the simulation method and for the approximation method.