• Title/Summary/Keyword: Statistical properties

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ON TRIPLE SEQUENCES IN GRADUAL 2-NORMED LINEAR SPACES

  • Isil Acik Demirci;Gulsum Dermencioglu
    • Honam Mathematical Journal
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    • v.46 no.2
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    • pp.291-306
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    • 2024
  • The concept of lacunary statistical convergence of triple sequences with respect to gradual 2-normed linear spaces is introduced in this research. We learn about its link to some inclusion and fundamental properties. The notion of lacunary statistical Cauchy triple sequences is introduced in the conclusion, and it is demonstrated that it is equivalent to the idea of lacunary statistical convergence.

Properties of Detection Matrix and Parallel Flats fraction for $3^n$ Search Design+

  • Um, Jung-Koog
    • Journal of the Korean Statistical Society
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    • v.13 no.2
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    • pp.114-120
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    • 1984
  • A parallel flats fraction for the $3^n$ design is defined as union of flats ${t}At=c_i(mod 3)}, i=1,2,\cdots, f$ and is symbolically written as At=C where A is rank r. The A matrix partitions the effects into n+1 alias sets where $u=(3^{n-r}-1)/2. For each alias set the f flats produce an ACPM from which a detection matrix is constructed. The set of all possible parallel flats fraction C can be partitioned into equivalence classes. In this paper, we develop some properties of a detection matrix and C.

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Some Stochastic Properties for Imperfect Repair Model

  • Lim, Jae-Hak;Park, Dong-Ho;Sohn, Joong-Kwon
    • Journal of the Korean Statistical Society
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    • v.28 no.3
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    • pp.389-398
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    • 1999
  • We consider an imperfect repair model under which either a perfect repair or a minimal repair can be performed at each failure of a unit. Some stochastic properties of the number of perfect repairs and the number of minimal repairs under the imperfect repair model are investigated. We also derive the expressions for evaluating the expected numbers of perfect and minimal repairs in general and apply these formulas for certain parametric families of life distributions.

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A Repair Process with Embedded Markov Chain

  • Lee, Eui-Yong;Munsup Seoh
    • Journal of the Korean Statistical Society
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    • v.28 no.4
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    • pp.515-522
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    • 1999
  • A repair process of a system consisting of both perfect repairs and minimal repairs is introduced. The type of repair, when the system fails, is determined by an embedded two state Markov chain. We study several stochastic properties of the process including the preservation of ageing properties and the monotonicities of the time between successive repairs. After assigning repair costs to the process, we also show that an optimal repair policy uniquely exists, if the underlying life distribution of the system has DMRL.

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The Mixing Properties of Subdiagonal Bilinear Models

  • Jeon, H.;Lee, O.
    • Communications for Statistical Applications and Methods
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    • v.17 no.5
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    • pp.639-645
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    • 2010
  • We consider a subdiagonal bilinear model and give sufficient conditions for the associated Markov chain defined by Pham (1985) to be uniformly ergodic and then obtain the $\beta$-mixing property for the given process. To derive the desired properties, we employ the results of generalized random coefficient autoregressive models generated by a matrix-valued polynomial function and vector-valued polynomial function.

ON BAYESIAN ESTIMATION AND PROPERTIES OF THE MARGINAL DISTRIBUTION OF A TRUNCATED BIVARIATE t-DISTRIBUTION

  • KIM HEA-JUNG;KIM Ju SUNG
    • Journal of the Korean Statistical Society
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    • v.34 no.3
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    • pp.245-261
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    • 2005
  • The marginal distribution of X is considered when (X, Y) has a truncated bivariate t-distribution. This paper mainly focuses on the marginal nontruncated distribution of X where Y is truncated below at its mean and its observations are not available. Several properties and applications of this distribution, including relationship with Azzalini's skew-normal distribution, are obtained. To circumvent inferential problem arises from adopting the frequentist's approach, a Bayesian method utilizing a data augmentation method is suggested. Illustrative examples demonstrate the performance of the method.

A STUDY ON THE EFFECT OF POWER TRANSFORMATION IN SPATIAL STATISTIC ANALYSIS

  • LEE JIN-HEE;SHIN KEY-IL
    • Journal of the Korean Statistical Society
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    • v.34 no.3
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    • pp.173-183
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    • 2005
  • The Box-Cox power transformation is generally used for variance stabilization. Recently, Shin and Kang (2001) showed, under the Box-Cox transformation, invariant properties to the original model under the large mean and relatively small variance assumptions in time series analysis. In this paper we obtain some invariant properties in spatial statistics. Spatial statistics, Invariant Property, Variogram, Box-Cox power Transformation.

Continuous Time Approximations to GARCH(1, 1)-Family Models and Their Limiting Properties

  • Lee, O.
    • Communications for Statistical Applications and Methods
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    • v.21 no.4
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    • pp.327-334
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    • 2014
  • Various modified GARCH(1, 1) models have been found adequate in many applications. We are interested in their continuous time versions and limiting properties. We first define a stochastic integral that includes useful continuous time versions of modified GARCH(1, 1) processes and give sufficient conditions under which the process is exponentially ergodic and ${\beta}$-mixing. The central limit theorem for the process is also obtained.

Effective Bandwidth for a Single Server Queueing System with Fractional Brownian Input

  • Kim, Sung-Gon;Nam, Seung-Yeob;Sung, Dan-Keun
    • Proceedings of the Korean Statistical Society Conference
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    • 2003.10a
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    • pp.1-8
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    • 2003
  • The traffic patterns of today's IP networks exhibit two important properties: self-similarity and long-range dependence. The fractional Brownian motion is widely used for representing the traffic model with the properties. We consider a single server fluid queueing system with input process of a fractional Brownian motion type. Formulas for effective bandwidth are derived in a single source and multiple source cases.

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Self-tuning Robust Regression Estimation

  • Park, You-Sung;Lee, Dong-Hee
    • Proceedings of the Korean Statistical Society Conference
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    • 2003.10a
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    • pp.257-262
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    • 2003
  • We introduce a new robust regression estimator, self-tuning regression estimator. Various robust estimators have been developed with discovery for theories and applications since Huber introduced M-estimator at 1960's. We start by announcing various robust estimators and their properties, including their advantages and disadvantages, and furthermore, new estimator overcomes drawbacks of other robust regression estimators, such as ineffective computation on preserving robustness properties.

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