• Title/Summary/Keyword: Data estimation

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Data-Dependent Choice of Optimal Number of Lags in Variogram Estimation

  • Choi, Seung-Bae;Kang, Chang-Wan;Cho, Jang-Sik
    • The Korean Journal of Applied Statistics
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    • v.23 no.3
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    • pp.609-619
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    • 2010
  • Geostatistical data among spatial data is analyzed in three stages: (1) variogram estimation, (2) model fitting for the estimated variograms and (3) spatial prediction using the fitted variogram model. It is very important to estimate the variograms properly as the first stage(i.e., variogram estimation) affects the next two stages. In general, the variogram is estimated with the moment estimator. To estimate the variogram, we have to decide the 'lag increment' or the 'number of lags'. However, there is no established rule for selecting the number of lags in estimating the variogram. The present paper proposes a method of choosing the optimal number of lags based on the PRESS statistic. To show the usefulness of the proposed method, we perform a small simulation study and show an empirical example with with air pollution data from Korea.

A Study of Observability Analysis and Data Fusion for Bias Estimation in a Multi-Radar System (다중 레이더 환경에서의 바이어스 오차 추정의 가관측성에 대한 연구와 정보 융합)

  • Won, Gun-Hee;Song, Taek-Lyul;Kim, Da-Sol;Seo, Il-Hwan;Hwang, Gyu-Hwan
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.8
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    • pp.783-789
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    • 2011
  • Target tracking performance improvement using multi-sensor data fusion is a challenging work. However, biases in the measurements should be removed before various data fusion techniques are applied. In this paper, a bias removing algorithm using measurement data from multi-radar tracking systems is proposed and evaluated by computer simulation. To predict bias estimation performance in various geometric relations between the radar systems and target, a system observability index is proposed and tested via computer simulation results. It is also studied that target tracking which utilizes multi-sensor data fusion with bias-removed measurements results in better performance.

Estimation in the exponential distribution under progressive Type I interval censoring with semi-missing data

  • Shin, Hyejung;Lee, Kwangho
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.6
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    • pp.1271-1277
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    • 2012
  • In this paper, we propose an estimation method of the parameter in an exponential distribution based on a progressive Type I interval censored sample with semi-missing observation. The maximum likelihood estimator (MLE) of the parameter in the exponential distribution cannot be obtained explicitly because the intervals are not equal in length under the progressive Type I interval censored sample with semi-missing data. To obtain the MLE of the parameter for the sampling scheme, we propose a method by which progressive Type I interval censored sample with semi-missing data is converted to the progressive Type II interval censored sample. Consequently, the estimation procedures in the progressive Type II interval censored sample can be applied and we obtain the MLE of the parameter and survival function. It will be shown that the obtained estimators have good performance in terms of the mean square error (MSE) and mean integrated square error (MISE).

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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A Study on Estimation and Factors of VHF Data Link Range (VHF 데이터통신 통달거리 예측 및 요소 분석)

  • Lee, Young-Joong;Kim, In-Seon;Park, Joo-Rae
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.3
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    • pp.413-420
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    • 2010
  • An Estimation of VHF data link range for EW(Electronic Warfare) equipment in the sea environment was studied to predict the data link range between transmitting and receiving station. The theoretical estimation predicts within 3% error with actual measurement of VHF data link range at sea. Data link range factors including refraction and reflection are added in the basic wave propagation equation. The effect of refraction and reflection to the range is analysed with quantity level.

Influence Analysis of Sampling Points on Accuracy of Storage Reliability Estimation for One-shot Systems (원샷 시스템의 저장 신뢰성 추정 정확성에 대한 샘플링 시점의 영향 분석)

  • Chung, Yong H.;Oh, Bong S.;Lee, Hong C.;Park, Hee N.;Jang, Joong S.;Park, Sang C.
    • Journal of Applied Reliability
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    • v.16 no.1
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    • pp.32-40
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    • 2016
  • Purpose: The purpose of this study is to analyze the effect of sampling points on accuracy of storage reliability estimation for one-shot systems by assuming a weibull distribution as a storage reliability distribution. Also propose method for determining of sampling points for increase the accuracy of reliability estimation. Methods: Weibull distribution was divided into three sections for confirming the possible to estimate the parameters of the weibull distribution only some section's sample. Generate quantal response data for failure data. And performed parameter estimation with quantal response data. Results: If reduce sample point interval of 1 section, increase the accuracy of reliability estimation although sampling only section 1. Even reduce total number of sampling point, reducing sampling time interval of the 1 zone improve the accuracy of reliability estimation. Conclusion: Method to increase the accuracy of reliability estimation is increasing number of sampling and the sampling points. But apply this method to One-shot system is difficult because test cost of one-shot system is expensive. So propose method of accuracy of storage reliability estimation of one-shot system by adjustment of the sampling point. And by dividing the section it could reduce the total sampling point.

Bayesian Estimation for the Multiple Regression with Censored Data : Mutivariate Normal Error Terms

  • Yoon, Yong-Hwa
    • Journal of the Korean Data and Information Science Society
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    • v.9 no.2
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    • pp.165-172
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    • 1998
  • This paper considers a linear regression model with censored data where each error term follows a multivariate normal distribution. In this paper we consider the diffuse prior distribution for parameters of the linear regression model. With censored data we derive the full conditional densities for parameters of a multiple regression model in order to obtain the marginal posterior densities of the relevant parameters through the Gibbs Sampler, which was proposed by Geman and Geman(1984) and utilized by Gelfand and Smith(1990) with statistical viewpoint.

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Channel Estimation Using Virtual Pilot Signal for MIMO-OFDM Systems (MIMO-OFDM 시스템을 위한 가상 기준 신호를 이용한 채널 추정 기법)

  • Seo, Heejin;Park, Sunho;Kim, Jinhong;Shim, Byonghyo
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.27 no.1
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    • pp.27-32
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    • 2016
  • In this paper, we proposed a soft decision-directed channel estimation based on MMSE estimation for MIMO-OFDM system. While the conventional method employs only pilot signals for channel estimation, the proposed algorithm performs channel estimation using pilot and reliable data signals. We also proposed selection criterion among reliable data signal for channel estimation. From numerical simulations, we show that the proposed channel estimator achieves 1 dB performance gain over conventional channel estimators.

A Study on the Change Factors by Activities for Estimating Historical Cost on Apartment Housing Projects (공동주택 실적공사비 산정시 공종별 변동요인에 관한 연구)

  • You, Yong-Hwan;Lee, Kyoo-Hyun;Kim, Chong-Woen;Choi, In-Seung
    • Journal of the Korea Institute of Building Construction
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    • v.4 no.4
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    • pp.117-126
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    • 2004
  • Construction industry is faced with the problems such as the quickly changeable circumstance and increasing construction companies due to regulation mollification of company registration. In order to overcome these problems, new estimation system based on historical estimation cost is ready to introduce by government step by step. But the time of transition for estimation system causes another problems such as chaos addition to simultaneity of a standard of estimation system and new estimation system, lack of related regulation, accumulation of historical extensive cost data, and adjustment methodology when historical estimation data is applied to next projects. The purpose of this study is to suggest the change factors by activities for estimating historical cost for apartment housing projects. New estimation system is based on historical construction data. For application of this system, the standard adjustment methodology system is necessary. and extensive cost data should be accumulated under an unified construction work classification system. Therefore in this study, according to the construction work classification system, every apartment housing project was classified to 16 work classifications, and 7 major composed items which occupy more than 85% of construction costs are analyzed by detailed activities and by average ratio and maximum ratio each of them. In the result of the study, furniture work, foundation work and masonry work are the works which have big gap of costs between average ration and maximum ratio. In addition to suggestion of change factor by work species, 5 qualified construction specialists are interviewed and change factors in 7 major works are analyzed.

Intelligent mobile Robot with RSSI based Indoor Location Estimation function (RSSI기반 위치인식기능 지능형 실내 자율 이동로봇)

  • Yoon, Ba-Da;Shin, Jae-Wook;Kim, Seong-Gil;Chung, Wan-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.10a
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    • pp.449-452
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    • 2007
  • An intelligent robot with RSSI based indoor location estimation function was designed and implemented. A wireless sensor node was attached to the robot to received the location data from the indoor location estimation function. Spartan III was used as the main control device in the mobile robot. The current location data collected from the indoor location estimation system was transferred to the mobile robot and server through Zigbee/IEEE 802.15.4 wireless communication of the sensor node. Once the location data is received, the sensor node senses the direction of the robot head and directs the robot to move to its destination. Indoor location estimation intelligent robot is able to move efficiently and actively to the user appointed location by implementing the proposed obstacles avoidance algorithm. This system is able to monitor real-time environmental data and location of the robot using PC program. Indoor location estimation intelligent robot also can be controlled by executing the instructions sent from the PC program.

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