• 제목/요약/키워드: efficient estimation

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Efficient Estimation of the Parameters of the Pareto Distribution in the Presence of Outliers

  • Dixit, U.J.;Jabbari Nooghabi, M.
    • Communications for Statistical Applications and Methods
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    • 제18권6호
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    • pp.817-835
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    • 2011
  • The moment(MM) and least squares(LS) estimations of the parameters are derived for the Pareto distribution in the presence of outliers. Further, we have derived a mixture method(MIX) of estimations with MM and LS that shows that the MIX is more efficient. In the final section we have given an example of actual data from a medical insurance company.

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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    • 제34권4호
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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.

이동 목표물의 효율적인 위치 추정을 위한 파티클 필터 신호 처리의 GPU 기반 가속화 (GPU-based Acceleration of Particle Filter Signal Processing for Efficient Moving-target Position Estimation)

  • 김성섭;조정훈;박대진
    • 대한임베디드공학회논문지
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    • 제12권5호
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    • pp.267-275
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    • 2017
  • Time of difference of arrival (TDOA) method using passive sonar sensor array has normally been used to estimate the location of a concealed moving target in underwater environment. Particle filter has been introduced for effective target estimation for non-Gaussian and nonlinear systems. In this paper, we propose a GPU-based acceleration of target position estimation using particle filter and propose efficient embedded system and software architecture. For the TDOA measurement from the passive sonar sensor, we use the generalized cross correlation phase transform (GCC-PHAT) method to obtain the correlation coefficient of the signal using FFT and we try to accelerate the calculation of GCC-PHAT based TDOA measurements using FFT with GPU CUDA. We also propose parallelization method of the target position estimation algorithm using the GPU CUDA to update the state of each particle for the target position estimation using the measured values. The target estimation algorithm was verified using Matlab and implemented using GPU CUDA. Then, we realized the proposed signal processing acceleration system using NVIDIA Jetson TX1 as the target board to analyze in terms of the execution time. The execution time of the algorithm is reduced by 55% to the CPU standalone-operation on the target board. Experiment results show that the proposed architecture is a feasible solution in terms of high-performance and area-efficient architecture.

비선형적 최소제곱법을 위한 효율적인 위치추정기법 (Efficient Localization Algorithm for Non-Linear Least Square Estimation)

  • 이정규;김영준;김성철
    • 한국통신학회논문지
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    • 제40권1호
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    • pp.88-95
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    • 2015
  • 본 논문은 비선형적 최소제곱법을 위한 효율적인 위치추정기법 연구를 하였다. 비선형적 최소제곱 방식은 선형적 최소제곱 방식에 비해 정확도가 높으며 거리 오차에 대해서 보다 강인한 추세를 보이지만 회기적인 방법을 취하기 때문에 계산 량이 매우 많아지는 단점이 있다. 본 논문에서는 비선형적 최소제곱 위치 추정 방식인 Newton method와 Levenberg-Marquardt 방식을 이용하였을 때 추정 위치 정확도와 복잡도 간의 기회비용 관점에서 효율적인 알고리즘을 제시하여 계산 량을 줄이면서 성능 열화를 방지할 수 있는 기법을 제시하였다. 시뮬레이션 결과로 추정 위치 정확도와 회기(iteration) 횟수를 구하고 선형적 방식의 위치 추정 성능, 기존의 비선형적 방식, 제안한 방식에 대해 비교 분석하여 제안한 알고리즘을 검증하였다.

On the Efficient Teaching Method of Confidence Interval in College Education

  • Kim, Yeung-Hoon;Ko, Jeong-Hwan
    • Journal of the Korean Data and Information Science Society
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    • 제19권4호
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    • pp.1281-1288
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    • 2008
  • The purpose of this study is to consider the efficient methods for introducing the confidence interval. We explain various concepts and approaches about the confidence interval estimation. Computing methods for calculating the efficient confidence interval are suggested.

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사회적 기업의 자료포락분석(DEA)을 통한 경영효율성 평가 (Management Efficiency Estimation of Social Enterprises with Data Envelopment Analysis)

  • 이상연;임성묵;채명신
    • 산업경영시스템학회지
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    • 제40권2호
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    • pp.121-128
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    • 2017
  • This paper was to evaluate social enterprises' management efficiency with Data Envelope Analysis (DEA). The data was based on the 168 social enterprises' of annual performance reports published in 2015. The research focused on to measure both financial efficiency and social impact of the companies simultaneously. To apply DEA, the paper classified the enterprises into seven types based on types of socal impacts which each company provides before the estimation of the efficiency. The research results showed that group D, which employes disadvantaged people, provides social services and shares resources was the most efficient group and had higest net worths in Pure Technical Efficiency. In contrast, Group B, which only employs social advantage people and provides social service, was the least efficient one. The research suggests a practical and efficient framework in measuring social enterprises' management efficiency, including both the financial performance and social impacts simultaneously with their self-publishing reports. Because the Korea Social Enterprise Promotion Agency does not open business reports which social enterprises submit each year, there are basic limitations on researchers attempting to analyse with data from all social enterprises in Korea. Thus, this study dealt with only 10% of the social enterprises which self-published their performance report on the Korea Social Enterprise Promotion Agency's web site. Regardless of these limitations, this study suggested substantial methods to estimate management efficiency with the self-published reports. Because self-publishing is increasing each year, it will be the main source of information for researchers in examining and evaluating social enterprises' financial performance or social contribution. The research suggests a practical and efficient framework in measuring social enterprises' management efficiency, including both the financial performance and social impacts simultaneously with their self-publishing reports. The research results suggest not only list of efficient enterprises but also methods of improvement for less efficient enterprises.

구조설계정보 통합 관리에 의한 철근 물량 산출 자동화 기초 연구 (Basic study about Automatic Rebar Quantity Estimation Integrated with Structural Design Information)

  • 성수진;임채연;김선국
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2015년도 춘계 학술논문 발표대회
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    • pp.109-110
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    • 2015
  • Estimation of rebar quantity may be used as an index to evaluate the economic feasibility of structural designs. However, when using the software to estimate the rebar quantity, there may be some limitations such as data loss caused by human errors and estimation delays caused by increased input time, since the information on arrangement of rebar is inserted manually. To solve the problems of such quantity estimation software, it is necessary to develop a method on automatic input/output of structural design information for quantity estimation and an algorithm for accurate estimation of rebar quantity. The purpose of this study is to improve the existing rebar quantity estimation by connecting with the database on information related to rebar estimation and the algorithm for rebar estimation, in order to develop an algorithm to estimate an accurate, net rebar quantity. The study result can be used as basic data for development of software for efficient structural designs and automatic framework estimation of buildings.

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Bayesian Parameter :Estimation and Variable Selection in Random Effects Generalised Linear Models for Count Data

  • Oh, Man-Suk;Park, Tae-Sung
    • Journal of the Korean Statistical Society
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    • 제31권1호
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    • pp.93-107
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    • 2002
  • Random effects generalised linear models are useful for analysing clustered count data in which responses are usually correlated. We propose a Bayesian approach to parameter estimation and variable selection in random effects generalised linear models for count data. A simple Gibbs sampling algorithm for parameter estimation is presented and a simple and efficient variable selection is done by using the Gibbs outputs. An illustrative example is provided.

모션 추정과 객체 추적을 이용한 이미지 깊이 검출기법 (A Technique of Image Depth Detection Using Motion Estimation and Object Tracking)

  • 조범석;김영로
    • 디지털산업정보학회논문지
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    • 제4권2호
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    • pp.15-19
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    • 2008
  • In this paper, we propose a new algorithm of image depth detection using motion estimation and object tracking. In industry, robots are used for automobile, conveyer system, etc. But, these have much necessary time. Thus, in this paper, we develop the efficient method of image depth detection based on motion estimation and object tracking.

쌍방향 움직임 예측을 이용한 움직임 보상 보간 기법에서 효율적인 움직임 벡터 보정 방법 (Efficient Motion Vector Correction Method m Motion Compensated Interpolation Technique Using Bilateral Motion Estimation)

  • 박지윤;이창우
    • 한국통신학회논문지
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    • 제34권7C호
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    • pp.687-696
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    • 2009
  • 동영상 신호의 프레임율 증가를 위해서 움직임 보상 보간(motion compensated interpolation) 기법이 많이 사용 된다. 특히 쌍방향 예측을 이용한 움직임 추정 기법은 움직임 추정 과정에서 빈 공간이나 겹쳐지는 문제를 해결함으로써 중간 삽입 프레임 생성 과정에서 좋은 성능을 보인다. 그러나 이와 같은 움직임 추정 과정에서 잘못된 움직임 벡터를 선택할 경우 왜곡된 블록을 생성할 수 있다. 본 논문에서는 쌍방향 움직임 예측을 기반으혹 하는 움직임 보상 보간 기법의 움직임 추정 과정에서 선택되는 움직임 벡터가 올바른 추정인지를 판별하고 인접한 움직임 벡터와 병함한 블록을 이용하여 1/2 화소 단위로 움직임 벡터를 보정하는 새로운 기법을 제안한다. 또한, 제안하는 기법이 기존의 움직임 벡터 추정 기법에 비해서 우수한 성능을 보이는 것을 모의 실험을 통하여 확인한다.