• Title/Summary/Keyword: sequential empirical process

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THE EMPIRICAL LIL FOR THE KAPLAN-MEIER INTEGRAL PROCESS

  • Bae, Jong-Sig;Kim, Sung-Yeun
    • Bulletin of the Korean Mathematical Society
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    • v.40 no.2
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    • pp.269-279
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    • 2003
  • We prove an empirical LIL for the Kaplan-Meier integral process constructed from the random censorship model under bracketing entropy and mild assumptions due to censoring effects. The main method in deriving the empirical LIL is to use a weak convergence result of the sequential Kaplan-Meier integral process whose proofs appear in Bae and Kim [2]. Using the result of weak convergence, we translate the problem of the Kaplan Meier integral process into that of a Gaussian process. Finally we derive the result using an empirical LIL for the Gaussian process of Pisier [6] via a method adapted from Ossiander [5]. The result of this paper extends the empirical LIL for IID random variables to that of a random censorship model.

THE LAWS OF THE ITERATED LOGARITHM FOR THE TENT MAP

  • Bae, Jongsig;Hwang, Changha;Jun, Doobae
    • Communications of the Korean Mathematical Society
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    • v.32 no.4
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    • pp.1067-1076
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    • 2017
  • This paper considers the asymptotic behaviors of the processes generated by the classical ergodic tent map that is defined on the unit interval. We develop a sequential empirical process and get the uniform version of law of iterated logarithm for the tent map by using the bracketing entropy method.

Reactor Coolant Pump Seal Monitoring System Using Statistical Modeling Techniques (통계적모델을 이용한 원자로냉각재펌프 밀봉장치 성능감시)

  • Lee, Song-Kyu;Chung, Chang-Kyu;Bae, Jong-Kil;Ahn, Sang-Ha
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2007.11a
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    • pp.1386-1390
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    • 2007
  • This paper presents the equipment condition monitoring technology for the process or the equipment using statistical techniques. The equipment condition monitoring system consists of an empirical model to estimate the expected sensor values of process variables and a diagnose model to detect the abnormal condition and to identify the root source of the problem. The empirical model is constructed by the analysis of historic data. The diagnose model uses the sequential probability ratio test (SPRT) technique. The monitoring system was tested with real operating data acquired from the Reactor Coolant Pump Seal in the Nuclear Power Plant. It can detect the system degradation or failure at the early stage since it is able to catch the subtle deviation of process variables from normal condition.

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THE SEQUENTIAL UNIFORM LAW OF LARGE NUMBERS

  • Bae, Jong-Sig;Kim, Sung-Yeun
    • Bulletin of the Korean Mathematical Society
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    • v.43 no.3
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    • pp.479-486
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    • 2006
  • Let $Z_n(s,\;f)=n^{-1}\;{\sum}^{ns}_{i=1}(f(X_i)-Pf)$ be the sequential empirical process based on the independent and identically distributed random variables. We prove that convergence problems of $sup_{(s,\;f)}|Z_n(s,\;f)|$ to zero boil down to those of $sup_f|Z_n(1,\;f)|$. We employ Ottaviani's inequality and the complete convergence to establish, under bracketing entropy with the second moment, the almost sure convergence of $sup_{(s,\;f)}|Z_n(s,\;f)|$ to zero.

A Study on Partial Pattern Estimation for Sequential Agglomerative Hierarchical Nested Model (SAHN 모델의 부분적 패턴 추정 방법에 대한 연구)

  • Jang, Kyung-Won;Ahn, Tae-Chon
    • Proceedings of the KIEE Conference
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    • 2005.10b
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    • pp.143-145
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    • 2005
  • In this paper, an empirical study result on pattern estimation method is devoted to reveal underlying data patterns with a relatively reduced computational cost. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). Conventional SAHN based clustering requires large computation time in the initial step of algorithm. To deal with this concern, we modified overall process with a partial approach. In the beginning of this method, we divide given data set to several sub groups with uniform sampling and then each divided sub data group is applied to SAHN based method. The advantage of this method reduces computation time of original process and gives similar results. Proposed is applied to several test data set and simulation result with conceptual analysis is presented.

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Development of ICT as an evolutionary process

  • Hwang, Gyu-hee
    • Journal of Korea Technology Innovation Society
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    • v.5 no.2
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    • pp.189-211
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    • 2002
  • The research shows how the technological change of 'Information and Communication Technology' (ICT) is accompanied with the usage change. It aims to provide a better conceptualization with empirical findings about the fact that the technological development of ICT is a convergence process of ICT factors with the usage of ICT moving from a limited coverage toward a general-purpose. The research adapts a descriptive methodology on a historical matter and demonstrates how it can be conducted through analytical description of Input-Output tables (I/O) the over periods. The case is about the UK with sequential I/O during 1970s- 90s.

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Migration Decision-Making Process-Synthesis of Macrolevel and Microlevel Perspectives (거주지 이동에 관한 모형의 설정-거시적 접근과 미시적 접근의 결합)

  • 정기원
    • Korea journal of population studies
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    • v.12 no.1
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    • pp.30-42
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    • 1989
  • This study develops a model of migration decision-making process, with identifying macrolevel and microlevel factors affecting the process. The model includes some sequential stages : to be dissatisfied with current residential area, intend to move, collect information about alternative destinations, select destination, decide to move, and make actual migration. The macrolevel factors included in the model are environmental, socioeconomic, cultural, and demographic characteristics of the current residence and alternative destinations. The microlevel factors are psychological, socioeconomic, and demographic characteristics of the individual. The effects of the macrolevel and microlevel factors on each stage of migration decision-making process are identified from the previous studies on migration. This study has both theoretical and practical implications. The theoretical contribution will be in the area of integrating the ecological and the individual level perspectives of migration by identifying the macrolevel and microlevel effects on migration decision-making process. This study also has implications for theoretical frameworks guiding empirical analysis of migration behavior of the individuals, and for policies aimed at redistributing population.

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THE UNIFORM CLT FOR MARTINGALE DIFFERENCE ARRAYS UNDER THE UNIFORMLY INTEGRABLE ENTROPY

  • Bae, Jong-Sig;Jun, Doo-Bae;Levental, Shlomo
    • Bulletin of the Korean Mathematical Society
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    • v.47 no.1
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    • pp.39-51
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    • 2010
  • In this paper we consider the uniform central limit theorem for a martingale-difference array of a function-indexed stochastic process under the uniformly integrable entropy condition. We prove a maximal inequality for martingale-difference arrays of process indexed by a class of measurable functions by a method as Ziegler [19] did for triangular arrays of row wise independent process. The main tools are the Freedman inequality for the martingale-difference and a sub-Gaussian inequality based on the restricted chaining. The results of present paper generalizes those of Ziegler [19] and other results of independent problems. The results also generalizes those of Bae and Choi [3] to martingale-difference array of a function-indexed stochastic process. Finally, an application to classes of functions changing with n is given.

Data Pattern Estimation with Movement of the Center of Gravity

  • Ahn Tae-Chon;Jang Kyung-Won;Shin Dong-Du;Kang Hak-Soo;Yoon Yang-Woong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.3
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    • pp.210-216
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    • 2006
  • In the rule based modeling, data partitioning plays crucial role be cause partitioned sub data set implies particular information of the given data set or system. In this paper, we present an empirical study result of the data pattern estimation to find underlying data patterns of the given data. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). In each sequence, the average value of the sum of all inter-distance between centroid and data point. In the sequel, compute the derivation of the weighted average distance to observe a pattern distribution. For the final step, after overall clustering process is completed, weighted average distance value is applied to estimate range of the number of clusters in given dataset. The proposed estimation method and its result are considered with the use of FCM demo data set in MATLAB fuzzy logic toolbox and Box and Jenkins's gas furnace data.