• Title/Summary/Keyword: Location parameter

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Estimation for a bivariate survival model based on exponential distributions with a location parameter

  • Hong, Yeon Woong
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.4
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    • pp.921-929
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    • 2014
  • A bivariate exponential distribution with a location parameter is proposed as a model for a two-component shared load system with a guarantee time. Some statistical properties of the proposed model are investigated. The maximum likelihood estimators and uniformly minimum variance unbiased estimators of the parameters, mean time to failure, and the reliability function of system are obtained with unknown guarantee time. Simulation studies are given to illustrate the results.

Reducing Bias of the Minimum Hellinger Distance Estimator of a Location Parameter

  • Pak, Ro-Jin
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.213-220
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    • 2006
  • Since Beran (1977) developed the minimum Hellinger distance estimation, this method has been a popular topic in the field of robust estimation. In the process of defining a distance, a kernel density estimator has been widely used as a density estimator. In this article, however, we show that a combination of a kernel density estimator and an empirical density could result a smaller bias of the minimum Hellinger distance estimator than using just a kernel density estimator for a location parameter.

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On the Effects of Plotting Positions to the Probability Weighted Moments Method for the Generalized Logistic Distribution

  • Kim, Myung-Suk
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.561-576
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    • 2007
  • Five plotting positions are applied to the computation of probability weighted moments (PWM) on the parameters of the generalized logistic distribution. Over a range of parameter values with some finite sample sizes, the effects of five plotting positions are investigated via Monte Carlo simulation studies. Our simulation results indicate that the Landwehr plotting position frequently tends to document smaller biases than others in the location and scale parameter estimations. On the other hand, the Weibull plotting position often tends to cause larger biases than others. The plotting position (i - 0.35)/n seems to report smaller root mean square errors (RMSE) than other plotting positions in the negative shape parameter estimation under small samples. In comparison to the maximum likelihood (ML) method under the small sample, the PWM do not seem to be better than the ML estimators in the location and scale parameter estimations documenting larger RMSE. However, the PWM outperform the ML estimators in the shape parameter estimation when its magnitude is near zero. Sensitivity of right tail quantile estimation regarding five plotting positions is also examined, but superiority or inferiority of any plotting position is not observed.

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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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.

Fault Diagnosis Algorithm for Linear Dynamic System (선형동적 시스템에서의 고장진단 알고리즘)

  • Moon, Bong Chae;Kim, Jee Hong;Kim, Byung Kook;Bien, Zeungnam
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.23 no.6
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    • pp.874-880
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    • 1986
  • A new diagnastic method for detection and location of faults in a linear time-invariant system is proposed. The fault detection algorithm is formulated in a signal space, while the fault location algorithm with estimation is done in a parameter space. In a way different from the conventional approach, the method of fault location with estimation is studied to apply the new concept to establish the models with an unknown parameter under the assumption of 1-fold fault. According to computer simulation, the proposed diagnostic method is effective as an algorithm for fault diagnosis of industdrial process controllers.

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Asymptotic properties of monitoring procedure for parameter change in heteroscedastic time series models (이분산 시계열 모형에서 모수의 변화에 대한 모니터링 절차의 점근 성질)

  • Kim, Soo Taek;Oh, Hae June
    • The Korean Journal of Applied Statistics
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    • v.33 no.4
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    • pp.467-482
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    • 2020
  • We investigate a monitoring procedure for the early detection of parameter changes in location-scale time series models. We introduce a detector for monitoring procedure based on modified residual cumulative sum (CUSUM). The asymptotic properties of the monitoring procedure are established under the null and alternative hypotheses. Simulation results and data analysis are also provided for illustration.

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.

Bayesian Parameter Estimation of the Four-Parameter Gamma Distribution

  • Oh, Mi-Ra;Kim, Kyung-Sook;Cho, Wan-Hyun;Son, Young-Sook
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.255-266
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    • 2007
  • A Bayesian estimation of the four-parameter gamma distribution is considered under the noninformative prior. The Bayesian estimators are obtained by the Gibbs sampling. The generation of the shape/power parameter and the power parameter in the Gibbs sampler is implemented using the adaptive rejection sampling algorithm of Gilks and Wild (1992). Also, the location parameter is generated using the adaptive rejection Metropolis sampling algorithm of Gilks, Best and Tan (1995). Finally, the simulation result is presented.

Bayesian Test for the Difference of Exponential Guarantee Time Parameters

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • 한국데이터정보과학회:학술대회논문집
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    • 2004.04a
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    • pp.15-23
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    • 2004
  • When X and Y have independent two parameter exponential distributions, we develop a Bayesian testing procedures for the equality of two location parameters. Under the noninformative prior, we propose a Bayesian test procedures for the equality of two location parameters using fractional Bayes factor and intrinsic Bayes factor. Simulation study and some real data examples are provided.

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