• Title/Summary/Keyword: stationary distribution

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Net Inventory Positions in Systems with Non-Stationary Poisson Demand Processes

  • Sung, Chang-Sup
    • Journal of the Korean Operations Research and Management Science Society
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    • v.6 no.2
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    • pp.51-55
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    • 1981
  • In both continuous-review and periodic-review non-stationary inventory systems, the non-stationary Poisson demand process and the associated inventory position processes were proved being mutually independent of each other, which lead to the probability distribution of the corresponding net inventory position process in the form of a finite product sum of those two process distributions. It is also discussed how these results can correspond to analytical stochastic inventory cost function formulations in terms of the probability distributions of the processes.

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Parameter Estimation in a Complex Non-Stationary and Nonlinear Diffusion Process

  • So, Beong-Soo
    • Journal of the Korean Statistical Society
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    • v.29 no.4
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    • pp.489-499
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    • 2000
  • We propose a new instrumental variable estimator of the complex parameter of a class of univariate complex-valued diffusion processes defined by the possibly non-stationary and/or nonlinear stochastic differential equations. On the basis of the exact finite sample distribution of the pivotal quantity, we construct the exact confidence intervals and the exact tests for the parameter. Monte-Carlo simulation suggests that the new estimator seems to provide a viable alternative to the maximum likelihood estimator (MLE) for nonlinear and/or non-stationary processes.

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A RECENT PROGRESS IN ALGORITHMIC ANALYSIS OF FIFO QUEUES WITH MARKOVIAN ARRIVAL STEAMS

  • Takine, Tetsuya
    • Journal of the Korean Mathematical Society
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    • v.38 no.4
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    • pp.807-842
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    • 2001
  • This paper summarizes recent development of analytical and algorithmical results for stationary FIFO queues with multiple Markovian arrival streams, where service time distributions are general and they may differ for different arrival streams. While this kind of queues naturally arises in considering queues with a superposition of independent phase-type arrivals, the conventional approach based on the queue length dynamics (i.e., M/G/1 pradigm) is not applicable to this kind of queues. On the contrary, the workload process has a Markovian property, so that it is analytically tractable. This paper first reviews the results for the stationary distributions of the amount of work-in-system, actual waiting time and sojourn time, all of which were obtained in the last six years by the author. Further this paper shows an alternative approach, recently developed by the author, to analyze the joint queue length distribution based on the waiting time distribution. An emphasis is placed on how to construct a numerically feasible recursion to compute the stationary queue length mass function.

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Reinforcement leaning based multi-echelon supply chain distribution planning (강화학습 기반의 다단계 공급망 분배계획)

  • Kwon, Ick-Hyun
    • Journal of the Korea Safety Management & Science
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    • v.16 no.4
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    • pp.323-330
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    • 2014
  • Various inventory control theories have tried to modelling and analyzing supply chains by using quantitative methods and characterization of optimal control policies. However, despite of various efforts in this research filed, the existing models cannot afford to be applied to the realistic problems. The most unrealistic assumption for these models is customer demand. Most of previous researches assume that the customer demand is stationary with a known distribution, whereas, in reality, the customer demand is not known a priori and changes over time. In this paper, we propose a reinforcement learning based adaptive echelon base-stock inventory control policy for a multi-stage, serial supply chain with non-stationary customer demand under the service level constraint. Using various simulation experiments, we prove that the proposed inventory control policy can meet the target service level quite well under various experimental environments.

Stochastic Upper Bound for the Stationary Queue Lengths of GPS Servers

  • Kim, Sung-Gon
    • The Korean Journal of Applied Statistics
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    • v.22 no.3
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    • pp.541-551
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    • 2009
  • Generalized processor sharing(GPS) service policy is a scheduling algorithm to allocate the bandwidth of a queueing system with multi-class input traffic. In a queueing system with single-class traffic, the stationary queue length becomes larger stochastically when the bandwidth (i.e. the service rate) of the system decreases. For a given GPS server, we consider the similar problem to this. We define the monotonicity for the head of the line processor sharing(HLPS) servers in which the units in the heads of the queues are served simultaneously and the bandwidth allocated to each queue are determined by the numbers of units in the queues. GPS is a type of monotonic HLPS. We obtain the HLPS server whose queue length of a class stochastically bounds upper that of corresponding class in the given monotonic HLPS server for all classes. The queue lengths process of all classes in the obtained HLPS server has the stationary distribution of product form. When the given monotonic HLPS server is GPS server, we obtain the explicit form of the stationary queue lengths distribution of the bounding HLPS server. Numerical result shows how tight the stochastic bound is.

ESTIMATION OF THE DISTRIBUTION FUNCTION FOR STATIONARY RANDOM FIELDS OF ASSOCIATED PROCESSES

  • Kim, Tae-Sung;Ko, Mi-Hwa;Yoo, Yeon-Sun
    • Communications of the Korean Mathematical Society
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    • v.19 no.1
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    • pp.169-177
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    • 2004
  • For a stationary field $\{X_{\b{j}},\b{j}{\;}\in{\;}{\mathbb{Z}}^d_{+}\}$ of associated random variables with distribution function $F(x)\;=\;P(X_{\b{1}}\;{\leq}\;x)$ we study strong consistency and asymptotic normality of the empirical distribution function, which is proposed as an estimator for F(x). We also consider strong consistency and asymptotic normality of the empirical survival function by applying these results.

Further study on the risk model with a continuous type investment (연속적으로 투자가 이루어지는 보험상품 리스크 모형의 추가 연구)

  • Choi, Seung Kyoung;Lee, Eui Yong
    • The Korean Journal of Applied Statistics
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    • v.31 no.6
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    • pp.751-759
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    • 2018
  • Cho et al. (Communications for Statistical Applications and Methods, 23, 423-432, 2016) introduced a risk model with a continuous type investment and studied the stationary distribution of the surplus process. In this paper, we extend the earlier analysis by assuming that additional instant investment is made when the surplus process reaches a certain sufficient level. We obtain the explicit form of the stationary distribution of the surplus process. The case is shown as an example, when the amount of claim is exponentially distributed.

Predicting of tall building response to non-stationary winds using multiple wind speed samples

  • Huang, Guoqing;Chen, Xinzhong;Liao, Haili;Li, Mingshui
    • Wind and Structures
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    • v.17 no.2
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    • pp.227-244
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    • 2013
  • Non-stationary extreme winds such as thunderstorm downbursts are responsible for many structural damages. This research presents a time domain approach for estimating along-wind load effects on tall buildings using multiple wind speed time history samples, which are simulated from evolutionary power spectra density (EPSD) functions of non-stationary wind fluctuations using the method developed by the authors' earlier research. The influence of transient wind loads on various responses including time-varying mean, root-mean-square value and peak factor is also studied. Furthermore, a simplified model is proposed to describe the non-stationary wind fluctuation as a uniformly modulated process with a modulation function following the time-varying mean. Finally, the probabilistic extreme response and peak factor are quantified based on the up-crossing theory of non-stationary process. As compared to the time domain response analysis using limited samples of wind record, usually one sample, the analysis using multiple samples presented in this study will provide more statistical information of responses. The time domain simulation also facilitates consideration of nonlinearities of structural and wind load characteristics over previous frequency domain analysis.

Flood Frequency Analysis Considering Probability Distribution and Return Period under Non-stationary Condition (비정상성 확률분포 및 재현기간을 고려한 홍수빈도분석)

  • Kim, Sang Ug;Lee, Yeong Seob
    • Journal of Korea Water Resources Association
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    • v.48 no.7
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    • pp.567-579
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    • 2015
  • This study performed the non-stationary flood frequency analysis considering time-varying parameters of a probability density function. Also, return period and risk under non-stationary condition were estimated. A stationary model and three non-stationary models using Generalized Extreme Value(GEV) were developed. The only location parameter was assumed as time-varying parameter in the first model. In second model, the only scale parameter was assumed as time-varying parameter. Finally, the both parameters were assumed as time varying parameter in the last model. Relative likelihood ratio test and Akaike information criterion were used to select appropriate model. The suggested procedure in this study was applied to eight multipurpose dams in South Korea. Using relative likelihood ratio test and Akaike information criterion it is shown that the inflow into the Hapcheon dam and the Seomjingang dam were suitable for non-stationary GEV model but the other six dams were suitable for stationary GEV model. Also, it is shown that the estimated return period under non-stationary condition was shorter than those estimated under stationary condition.

Thermodynamic Properties of the Solute Transfer from the Aqueous Acetonitrile Mobile Phase to the Stationary Phase Monitored by HPLC

  • Jeong, Won Jo;Kim, Ji Yeon;Gu, Yun Mo
    • Bulletin of the Korean Chemical Society
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    • v.21 no.1
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    • pp.105-109
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    • 2000
  • High-performance liquid chromatography is suitable for getting thermodynamic information about solute-solvent interactions. We used a squalane impregnated $C_{18}$ phase as a presumably bulk-like stationary phase to secure a simple partition mechanism for solute retention in reversed phase liquid chromatographic system. We measured retention data of some selected solutes (benzene, toluene, ethylbenzene, propylbenzene, butylbenzene, phenol, benzylalcohol, phenethylalcohol, benzylacetone, acetophenone, benzonitrile, benzylcyanide) at 25, 30, 35, 40, 45, and 50 $^{\circ}C$ in 30/70, 40/60, 50/50, 60/40 and 70/30 (v/v%) acetonitrile/water eluents. The van't Hoff plots were nicely linear, thus we calculated dependable thermodynamic values such as enthalpies and entropies of solute transfer from the mobile phase to the stationary phase based on more than four retention measurements on different days (or weeks). We found that the cavity formation effect was the major factor in solute distribution between the mobile and stationary phases in the system studied here. Our data were com-pared with some relevant literature data.