• 제목/요약/키워드: identically distributed

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A Kernel-function-based Approach to Sequential Estimation with $\beta$-protection of Quantiles

  • 김성래;김성균
    • 한국전산응용수학회:학술대회논문집
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    • 한국전산응용수학회 2003년도 KSCAM 학술발표회 프로그램 및 초록집
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    • pp.14-14
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    • 2003
  • Given a sequence { $X_{n}$} of independent and identically distributed random variables with F, a sequential procedure for the p-th quantile ξ$_{P}$= $F^{-1}$ (P), 0$\beta$-protection. Some asymptotic properties for the proposed procedure and of an involved stopping time are proved: asymptotic consistency, asymptotic efficiency and asymptotic normality. From one of the results an effect of smoothing based on kernel functions is discussed. The results are also extended to the contaminated case.e.e.

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망목특성을 갖는 제품의 공차 설계에서 제한된 생산 용량의 효과 분석 (Effects of Limited Capacity on Tolerance Design for Products With N-Type Quality Characteristics)

  • 최익준;홍성훈
    • 품질경영학회지
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    • 제36권2호
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    • pp.20-27
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    • 2008
  • Tolerance design has been identified as an important research area and a number of models have been proposed in the literature. This paper investigates the effect of limited capacity on tolerance design for products with nominal-the-best type (N-type) quality characteristics. The model is developed under the assumption that the reprocessed and nonreprocessed items are produced by the same manufacturing process and therefore their quality characteristics are identically and independently distributed. Profit models are constructed which involve four price/cost components; selling price, cost incurred by imperfect quality, reprocessing and quality inspection costs. Methods of finding the optimal tolerance limits are presented, and a numerical example is given. Sensitivity analyses are also performed to study the effect of a process standard deviation on this model.

Two Sample Test Procedures for Linear Rank Statistics for Garch Processes

  • Chandra S. Ajay;Vanualailai Jito;Raj Sushil D.
    • Communications for Statistical Applications and Methods
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    • 제12권3호
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    • pp.557-587
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    • 2005
  • This paper elucidates the limiting Gaussian distribution of a class of rank order statistics {$T_N$} for two sample problem pertaining to empirical processes of the squared residuals from two independent samples of GARCH processes. A distinctive feature is that, unlike the residuals of ARMA processes, the asymptotics of {$T_N$} depend on those of GARCH volatility estimators. Based on the asymptotics of {$T_N$}, we empirically assess the relative asymptotic efficiency and effect of the GARCH specification for some GARCH residual distributions. In contrast with the independent, identically distributed or ARMA settings, these studies illuminate some interesting features of GARCH residuals.

ON THE STRONG LAW OF LARGE NUMBERS FOR WEIGHTED SUMS OF ARRAYS OF ROWWISE NEGATIVELY DEPENDENT RANDOM VARIABLES

  • Baek, Jong-Il;Seo, Hye-Young;Lee, Gil-Hwan;Choi, Jeong-Yeol
    • 대한수학회지
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    • 제46권4호
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    • pp.827-840
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    • 2009
  • Let {$X_{ni}$ | $1{\leq}i{\leq}n,\;n{\geq}1$} be an array of rowwise negatively dependent (ND) random variables. We in this paper discuss the conditions of ${\sum}^n_{t=1}a_{ni}X_{ni}{\rightarrow}0$ completely as $n{\rightarrow}{\infty}$ under not necessarily identically distributed setting and the strong law of large numbers for weighted sums of arrays of rowwise negatively dependent random variables is also considered.

CONDITIONAL CENTRAL LIMIT THEOREMS FOR A SEQUENCE OF CONDITIONAL INDEPENDENT RANDOM VARIABLES

  • Yuan, De-Mei;Wei, Li-Ran;Lei, Lan
    • 대한수학회지
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    • 제51권1호
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    • pp.1-15
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    • 2014
  • A conditional version of the classical central limit theorem is derived rigorously by using conditional characteristic functions, and a more general version of conditional central limit theorem for the case of conditionally independent but not necessarily conditionally identically distributed random variables is established. These are done anticipating that the field of conditional limit theory will prove to be of significant applicability.

A New Integral Representation of the Coverage Probability of a Random Convex Hull

  • Son, Won;Ng, Chi Tim;Lim, Johan
    • Communications for Statistical Applications and Methods
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    • 제22권1호
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    • pp.69-80
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    • 2015
  • In this paper, the probability that a given point is covered by a random convex hull generated by independent and identically-distributed random points in a plane is studied. It is shown that such probability can be expressed in terms of an integral that can be approximated numerically by function-evaluations over the grid-points in a 2-dimensional space. The new integral representation allows such probability be computed efficiently. The computational burdens under the proposed integral representation and those in the existing literature are compared. The proposed method is illustrated through numerical examples where the random points are drawn from (i) uniform distribution over a square and (ii) bivariate normal distribution over the two-dimensional Euclidean space. The applications of the proposed method in statistics are are discussed.

THE CONTINUOUS DENSITY FUNCTION OF THE LIMITING SPECTRAL DISTRIBUTION

  • Choi, Sang-Il
    • Journal of applied mathematics & informatics
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    • 제28권1_2호
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    • pp.515-521
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    • 2010
  • In multivariate analysis, the inversion formula of the Stieltjes transform is used to find the density of a spectral distribution of random matrices of sample covariance type. Let $B_n\;=\;\frac{1}{N}Y_nY_n^TT_n$ where $Y_n\;=\;[Y_{ij}]_{n\;{\times}\;N}$ is with independent, identically distributed entries and $T_n$ is an $n\;{\times}\;n$ symmetric non-negative definite random matrix independent of the $Y_{ij}$'s. In the present paper, using the inversion formula of the Stieltjes transform, we will find that the limiting distribution of $B_n$ has a continuous density function away from zero.

Reweighted L1 Minimization for Compressed Sensing

  • 이혁;박선호;심병효
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2010년도 하계학술대회
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    • pp.61-63
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    • 2010
  • Recent work in compressed sensing theory shows that m${\times}$n independent and identically distributed sensing matrices whose entries are drawn independently from certain probability distributions guarantee exact recovery of a sparse signal with high probability even if m${\ll}$n. In particular, it is well understood that the L1 minimization algorithm is able to recover sparse signals from incomplete measurements. In this paper, we propose a novel sparse signal reconstruction method that is based on the reweighted L1 minimization via support recovery.

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An One-for-One Ordering Inventory Policy with Poisson Demands and Losses with Order Dependent Leadtimes

  • Choi, Jin-Yeong;Kim, Man-Sik
    • 한국경영과학회지
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    • 제12권1호
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    • pp.27-33
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    • 1987
  • A stochastic model for an inventory system in which depletion of stock takes place due to random demand as well as random loss of items is studied under the assumption that the intervals between cussessive unit demands as well as those between cussessive unit losses, are independently and identically distributed random variables having negative exponential distributions with respective parameters .mu. and .lambda. It is further assumed that leadtime for each order is an outstanding-order-dependent random variable. The steady state probability distribution of the net inventory level is derived under the continuous review (S -1, S) inventory policy, from which the total expected coast expression is formulated.

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ON A CHARACTERIZATION OF THE EXPONENTIAL DISTRIBUTION BY CONDITIONAL EXPECTATIONS OF RECORD VALUES

  • Lee, Min-Young
    • 대한수학회논문집
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    • 제16권2호
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    • pp.287-290
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    • 2001
  • Let X$_1$, X$_2$, … be a sequence of independent and identically distributed random variables with continuous cumulative distribution function F(x). X(sub)j is an upper record value of this sequence if X(sub)j > max {X$_1$, X$_2$, …, X(sub)j-1}. We define u(n) = min {j│j > u(n-1), X(sub)j > X(sub)u(n-1), n $\geq$ 2} with u(1) = 1. Then F(x) = 1 - e(sup)-x/c, x > 0 if and only if E[X(sub)n(n+1) - X(sub)u(n)│X(sub)u(m) = y] = c or E[X(sub)u(n+2) - X(sub)u(n)│X(sub)u(m) = y] = 2c, n $\geq$ m+1.

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