• Title/Summary/Keyword: independent identically distributed

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GEOMETRIC ERGODICITY AND TRANSIENCE FOR NONLINEAR AUTOREGRESSIVE MONELS

  • Lee, Oe-Sook
    • Communications of the Korean Mathematical Society
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    • v.10 no.2
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    • pp.409-417
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    • 1995
  • We consider the $R^k$-valued $(k \geq 1)$ process ${X_n}$ generated by $X_n + 1 = f(X_n)+e_{n+1}$, where $f(x) = (h(x),x^{(1)},x^{(1)},\cdots,x{(k-1)})'$. We assume that h is a real-valued measuable function on $R^k$ and that $e_n = (e'_n,0,\cdot,0)'$ where ${e'_n}$ are independent and identically distributed random variables. We obtained a practical criteria guaranteeing a given process to be geometrically ergodic. Sufficient condition for transience is also given.

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CONVERGENCE RATES FOR THE MOMENTS OF EXTREMES

  • Peng, Zuoxiang;Nadarajah, Saralees
    • Bulletin of the Korean Mathematical Society
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    • v.49 no.3
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    • pp.495-510
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    • 2012
  • Let $X_1$, $X_2$,${\ldots}$, $X_n$ be a sequence of independent and identically distributed random variables with common distribution function $F$. Convergence rates for the moments of extremes are studied by virtue of second order regularly conditions. A unified treatment is also considered under second order von Mises conditions. Some examples are given to illustrate the results.

CONVERGENCE RATE OF EXTREMES FOR THE GENERALIZED SHORT-TAILED SYMMETRIC DISTRIBUTION

  • Lin, Fuming;Peng, Zuoxiang;Yu, Kaizhi
    • Bulletin of the Korean Mathematical Society
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    • v.53 no.5
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    • pp.1549-1566
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    • 2016
  • Denote $M_n$ the maximum of n independent and identically distributed variables from the generalized short-tailed symmetric distribution. This paper shows the pointwise convergence rate of the distribution of $M_n$ to exp($\exp(-e^{-x})$) and the supremum-metric-based convergence rate as well.

On Optimal Estimates of System Reliability (시스템 신뢰성(信賴性)의 최적추정(最適推定))

  • Kim, Jae-Ju
    • Journal of Korean Society for Quality Management
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    • v.7 no.2
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    • pp.7-10
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    • 1979
  • In this paper the Rao-Blackwell and Lehmann-$Scheff{\acute{e}}$ Theorem are used to drive the minimum variance unbiased estimators of system reliability for a number of distributions when a system consists of n Components whose random life times are assumed to be independent and identically distributed. For the case of a negative exponential life time, we obtain the maximum likelihood estimator of the system reliability and compair it with minimum variance unbiased estimator of the system reliability.

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A Note on Central Limit Theorem on $L^P(R)$

  • Sungho Lee;Dug Hun Hong
    • 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 $L^P(R)$.

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ON THE RATIO X/(X + Y) FOR WEIBULL AND LEVY DISTRIBUTIONS

  • ALI M. MASOOM;NADARAJAH SARALEES;WOO JUNGSOO
    • 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.

Strong Representations for LAD Estimators in AR(1) Models

  • Kang, Hee-Jeong;Shin, Key-Il
    • 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.

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THE MINIMUM VARIANCE UNBIASED ESTIMATION OF SYSTEM RELIABILITY

  • Park, C.J.;Kim, Jae-Joo
    • 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.

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