• Title/Summary/Keyword: Parameter Management

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Reliability and ratio in exponentiated complementary power function distribution

  • Moon, Yeung-Gil;Lee, Chang-Soo;Ryu, Se-Gi
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.5
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    • pp.955-960
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    • 2009
  • As we shall dene an exponentiated complementary power function distribution, we shall consider moments, hazard rate, and inference for parameter in the distribution. And we shall consider an inference of the reliability and distributions for the quotient and the ratio in two independent exponentiated complementary power function random variables.

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A correction of SE from penalized partial likelihood in frailty models

  • Ha, Il-Do
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.5
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    • pp.895-903
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    • 2009
  • The penalized partial likelihood based on restricted maximum likelihood method has been widely used for the inference of frailty models. However, the standard-error estimate for frailty parameter estimator can be downwardly biased. In this paper we show that such underestimation can be corrected by using hierarchical likelihood. In particular, the hierarchical likelihood gives a statistically efficient procedure for various random-effect models including frailty models. The proposed method is illustrated via a numerical example and simulation study. The simulation results demonstrate that the corrected standard-error estimate largely improves such bias.

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OBJECTIVE BAYESIAN APPROACH TO STEP STRESS ACCELERATED LIFE TESTS

  • Kim Dal-Ho;Lee Woo-Dong;Kang Sang-Gil
    • Journal of the Korean Statistical Society
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    • v.35 no.3
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    • pp.225-238
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    • 2006
  • This paper considers noninformative priors for the scale parameter of exponential distribution when the data are collected in step stress accelerated life tests. We find the Jeffreys' and reference priors for this model and show that the reference prior satisfies first order matching criterion. Also, we show that there exists no second order matching prior in this problem. Some simulation results are given and we perform Bayesian analysis for proposed priors using some data.

Construction of Optimal Designs for Blocked Complete Diallel Crosses

  • Kim, Jin;Bae, Jong Sung;Han, Wean Sik;Kim, Seo Young
    • Communications for Statistical Applications and Methods
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    • v.9 no.2
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    • pp.337-346
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    • 2002
  • Complete diallel crosses using group divisible design with m=2 or n=2 and ${\lambda}_1$<${\lambda}_2$ as parameter designs become A-optimal, D-optimal designs. In case of ${\lambda}_2$=${\lambda}_1$+1, this blocked complete diallel crosses become generalized optimal designs.

INFERENCE ON THE SEASONALLY COINTEGRATED MODEL WITH STRUCTURAL CHANGES

  • Song, Dae-Gun;Cho, Sin-Sup
    • Journal of the Korean Statistical Society
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    • v.36 no.4
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    • pp.501-522
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    • 2007
  • We propose an estimation procedure that can be used for detecting structural changes in the seasonal cointegrated vector autoregressive model. The asymptotic properties of the estimates and the test statistics for the parameter change are provided. A simulation example is presented to illustrate this method and its concept.

Mobile Location Estimation for WCDMA System (WCDMA 시스템에서의 이동체 위치 추정 방안)

  • Lee, Jong-Chan;Lee, Moon-Ho
    • Journal of Information Technology Applications and Management
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    • v.14 no.4
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    • pp.1-16
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    • 2007
  • In the microcell- or picocell-based system the frequent movements of the mobile bring about excessive traffics into the networks. A mobile location estimation mechanism can facilitate both efficient resource allocation and better QoS provisioning through handoff optimization. Existing location estimation schemes consider only LOS model and have poor performance in presence of multi-path and shadowing. In this paper we study a novel scheme which can increase estimation accuracy by considering NLOS environment and other multiple decision parameters than the received signal strength.

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Dam Sensor Outlier Detection using Mixed Prediction Model and Supervised Learning

  • Park, Chang-Mok
    • International journal of advanced smart convergence
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    • v.7 no.1
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    • pp.24-32
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    • 2018
  • An outlier detection method using mixed prediction model has been described in this paper. The mixed prediction model consists of time-series model and regression model. The parameter estimation of the prediction model was performed using supervised learning and a genetic algorithm is adopted for a learning method. The experiments were performed in artificial and real data set. The prediction performance is compared with the existing prediction methods using artificial data. Outlier detection is conducted using the real sensor measurements in a dam. The validity of the proposed method was shown in the experiments.

Lifetime Performance Index for Weibull Distribution: Estimation and Applications (와이블 분포를 따를 때 수명성능지수의 추정과 활용)

  • Seo, Sun-Keun
    • Journal of Applied Reliability
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    • v.13 no.3
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    • pp.191-206
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    • 2013
  • Application areas for Lifetime Performance Index(LPI), a kind of process capability index to be frequently used as a means of measuring process performance are illustrated with examples. Statistical properties for maximum likelihood and unbiased estimators of LPI are evaluated and discussed under Weibull distribution with known shape parameter. Furthermore, guidelines for selecting an estimator of LPI are also presented.

Comparative Analysis of the characteristics of Ni-rich LIB according to temperature change (온도 변화에 따른 Ni-rich LIB의 설계인자별 파라미터 특성 비교 분석)

  • Gwon, Sun-Jong;Im, Ji-Hun;Choe, Jin-Hyeok;Kim, Jong-Hun
    • Proceedings of the KIPE Conference
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    • 2018.11a
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    • pp.131-132
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    • 2018
  • The world market for BESS (Battery Energy Storage System) is growing rapidly, and battery technology is also developing. It is important to understand the battery characteristics and develop a control strategy to develop the optimal BMS (Battery Management System). In this paper, we compare and analyze the parameter characteristics of NCM LIB (Lithium Ion Battery) according to the temperature change.

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Exploring the Possibilities of Operation Data Use for Data-Driven Management in National R&D API Management System (데이터 기반 경영을 위한 국가R&D API관리시스템의 운영 데이터 활용 가능성 탐색)

  • Na, Hye-In;Lee, Jun-Young;Lee, Byeong-Hee;Choi, Kwang-Nam
    • The Journal of the Korea Contents Association
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    • v.20 no.4
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    • pp.14-24
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    • 2020
  • This paper aims to establish an efficient national R&D Application Programming Interface (API) management system for national R&D data-driven management and explore the possibility of using operational data according to the recent global data openness and sharing policy. In accordance with the trend of opening and sharing of national R&D data, we plan to improve management efficiency by analyzing operational data of the national R&D API service. For this purpose, we standardized the parameters for the national R&D APIs that were distributed separately by integrating the individual APIs to build a national R&D API management system. The results of this study revealed that the service call traffic of the national R&D API has shown 554.5% growth in the year as compared to the year 2015 when the measurement started. In addition, this paper also evaluations the possibility of using operational data through data preparation, analysis, and prediction based on service operations management data in the actual operation of national R&D integrated API management system.