• Title/Summary/Keyword: stationary distribution

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Analysis of Generalized Extreme Value Distribution to Estimate Storm Sewer Capacity Under Climate Change (기후변화에 따른 하수관거시설의 계획우수량 산정을 위한 일반극치분포 분석)

  • Lee, Hak-Pyo;Ryu, Jae-Na;Yu, Soon-Yu;Park, Kyoo-Hong
    • Journal of Korean Society of Water and Wastewater
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    • v.26 no.2
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    • pp.321-329
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    • 2012
  • In this study, statistical analysis under both stationary and non-stationary climate was conducted for rainfall data measured in Seoul. Generalised Extreme Value (GEV) distribution and Gumbel distribution were used for the analysis. Rainfall changes under the non-stationary climate were estimated by applying time variable (t) to location parameter (${\xi}$). Rainfall depths calculated in non-stationary climate increased by 1.1 to 6.2mm and 1.0 to 4.6mm for the GEV distribution and gumbel distribution respectively from those stationary forms. Changes in annual maximum rainfall were estimated with rate of change in the location parameter (${\xi}1{\cdot}t$), and temporal changes of return period were predicted. This was also available for re-evaluating the current sewer design return period. Design criteria of sewer system was newly suggested considering life expectance of the system as well as temporal changes in the return period.

M/PH/1 QUEUE WITH DETERMINISTIC IMPATIENCE TIME

  • Kim, Jerim;Kim, Jeongsim
    • Communications of the Korean Mathematical Society
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    • v.28 no.2
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    • pp.383-396
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    • 2013
  • We consider an M/PH/1 queue with deterministic impatience time. An exact analytical expression for the stationary distribution of the workload is derived. By modifying the workload process and using Markovian structure of the phase-type distribution for service times, we are able to construct a new Markov process. The stationary distribution of the new Markov process allows us to find the stationary distribution of the workload. By using the stationary distribution of the workload, we obtain performance measures such as the loss probability, the waiting time distribution and the queue size distribution.

On Weak Convergence of Some Rescaled Transition Probabilities of a Higher Order Stationary Markov Chain

  • Yun, Seok-Hoon
    • Journal of the Korean Statistical Society
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    • v.25 no.3
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    • pp.313-336
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    • 1996
  • In this paper we consider weak convergence of some rescaled transi-tion probabilities of a real-valued, k-th order (k $\geq$ 1) stationary Markov chain. Under the assumption that the joint distribution of K + 1 consecutive variables belongs to the domain of attraction of a multivariate extreme value distribution, the paper gives a sufficient condition for the weak convergence and characterizes the limiting distribution via the multivariate extreme value distribution.

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Existence Condition for the Stationary Ergodic New Laplace Autoregressive Model of order p-NLAR(p)

  • Kim, Won-Kyung;Lynne Billard
    • Journal of the Korean Statistical Society
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    • v.26 no.4
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    • pp.521-530
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    • 1997
  • The new Laplace autoregressive model of order 2-NLAR92) studied by Dewald and Lewis (1985) is extended to the p-th order model-NLAR(p). A necessary and sufficient condition for the existence of an innovation sequence and a stationary ergodic NLAR(p) model is obtained. It is shown that the distribution of the innovation sequence is given by the probabilistic mixture of independent Laplace distributions and a degenrate distribution.

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Prediction of Return Periods of Sewer Flooding Due to Climate Change in Major Cities (기후변화에 따른 주요 도시의 하수도 침수 재현기간 예측)

  • Park, Kyoohong;Yu, Soonyu;Byambadorj, Elbegjargal
    • Journal of Korean Society of Water and Wastewater
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    • v.30 no.1
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    • pp.41-49
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    • 2016
  • In this study, rainfall characteristics with stationary and non-stationary perspectives were analyzed using generalized extreme value (GEV) distribution and Gumbel distribution models with rainfall data collected in major cities of Korea to reevaluate the return period of sewer flooding in those cities. As a result, the probable rainfall for GEV and Gumbel distribution in non-stationary state both increased with time(t), compared to the stationary probable rainfall. Considering the reliability of ${\xi}_1$, a variable reflecting the increase of storm events due to climate change, the reliability of the rainfall duration for Seoul, Daegu, and Gwangju in the GEV distribution was over 90%, indicating that the probability of rainfall increase was high. As for the Gumbel distribution, Wonju, Daegu, and Gwangju showed the higher reliability while Daejeon showed the lower reliability than the other cities. In addition, application of the maximum annual rainfall change rate (${\xi}_1{\cdot}t$) to the location parameter made possible the prediction of return period by time, therefore leading to the evaluation of design recurrence interval.

Application of a Non-stationary Frequency Analysis Method for Estimating Probable Precipitation in Korea (전국 확률강수량 산정을 위한 비정상성 빈도해석 기법의 적용)

  • Kim, Gwang-Seob;Lee, Gi-Chun
    • Journal of The Korean Society of Agricultural Engineers
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    • v.54 no.5
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    • pp.141-153
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    • 2012
  • In this study, we estimated probable precipitation amounts at the target year (2020, 2030, 2040) of 55 weather stations in Korea using the 24 hour annual maximum precipitation data from 1973 through 2009 which should be useful for management of agricultural reservoirs. Not only trend tests but also non-stationary tests were performed and non-stationary frequency analysis were conducted to all of 55 sites. Gumbel distribution was chosen and probability weighted moment method was used to estimate model parameters. The behavior of the mean of extreme precipitation data, scale parameter, and location parameter were analyzed. The probable precipitation amount at the target year was estimated by a non-stationary frequency analysis using the linear regression analysis for the mean of extreme precipitation data, scale parameter, and location parameter. Overall results demonstrated that the probable precipitation amounts using the non-stationary frequency analysis were overestimated. There were large increase of the probable precipitation amounts of middle part of Korea and decrease at several sites in Southern part. The non-stationary frequency analysis using a linear model should be applicable to relatively short projection periods.

STATIONARY SOLUTIONS FOR ITERATED FUNCTION SYSTEMS CONTROLLED BY STATIONARY PROCESSES

  • Lee, O.;Shin, D.W.
    • Journal of the Korean Mathematical Society
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    • v.36 no.4
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    • pp.737-746
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    • 1999
  • We consider a class of discrete parameter processes on a locally compact Banach space S arising from successive compositions of strictly stationary random maps with state space C(S,S), where C(S,S) is the collection of continuous functions on S into itself. Sufficient conditions for stationary solutions are found. Existence of pth moments and convergence of empirical distributions for trajectories are proved.

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EFFICIENT ESTIMATION OF THE COINTEGRATING VECTOR IN ERROR CORRECTION MODELS WITH STATIONARY COVARIATES

  • Seo, Byeong-Seon
    • Journal of the Korean Statistical Society
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    • v.34 no.4
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    • pp.345-366
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    • 2005
  • This paper considers the cointegrating vector estimator in the error correction model with stationary covariates, which combines the stationary vector autoregressive model and the nonstationary error correction model. The cointegrating vector estimator is shown to follow the locally asymptotically mixed normal distribution. The variance of the estimator depends on the co­variate effect of stationary regressors, and the asymptotic efficiency improves as the magnitude of the covariate effect increases. An economic application of the money demand equation is provided.

Stationary distribution of the surplus process in a risk model with a continuous type investment

  • Cho, Yang Hyeon;Choi, Seung Kyoung;Lee, Eui Yong
    • Communications for Statistical Applications and Methods
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    • v.23 no.5
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    • pp.423-432
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    • 2016
  • In this paper, we stochastically analyze the continuous time surplus process in a risk model which involves a continuous type investment. It is assumed that the investment of the surplus to other business is continuously made at a constant rate, while the surplus process stays over a given sufficient level. We obtain the stationary distribution of the surplus level and/or its moment generating function by forming martingales from the surplus process and applying the optional sampling theorem to the martingales and/or by establishing and solving an integro-differential equation for the distribution function of the surplus level.

WEAK CONVERGENCE FOR STATIONARY BOOTSTRAP EMPIRICAL PROCESSES OF ASSOCIATED SEQUENCES

  • Hwang, Eunju
    • Journal of the Korean Mathematical Society
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    • v.58 no.1
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    • pp.237-264
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    • 2021
  • In this work the stationary bootstrap of Politis and Romano [27] is applied to the empirical distribution function of stationary and associated random variables. A weak convergence theorem for the stationary bootstrap empirical processes of associated sequences is established with its limiting to a Gaussian process almost surely, conditionally on the stationary observations. The weak convergence result is proved by means of a random central limit theorem on geometrically distributed random block size of the stationary bootstrap procedure. As its statistical applications, stationary bootstrap quantiles and stationary bootstrap mean residual life process are discussed. Our results extend the existing ones of Peligrad [25] who dealt with the weak convergence of non-random blockwise empirical processes of associated sequences as well as of Shao and Yu [35] who obtained the weak convergence of the mean residual life process in reliability theory as an application of the association.