• Title/Summary/Keyword: 분산추정량

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Impact of Heterogeneous Dispersion Parameter on the Expected Crash Frequency (이질적 과분산계수가 기대 교통사고건수 추정에 미치는 영향)

  • Shin, Kangwon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.9
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    • pp.5585-5593
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    • 2014
  • This study tested the hypothesis that the significance of the heterogeneous dispersion parameter in safety performance function (SPF) used to estimate the expected crashes is affected by the endogenous heterogeneous prior distributions, and analyzed the impacts of the mis-specified dispersion parameter on the evaluation results for traffic safety countermeasures. In particular, this study simulated the Poisson means based on the heterogeneous dispersion parameters and estimated the SPFs using both the negative binomial (NB) model and the heterogeneous negative binomial (HNB) model for analyzing the impacts of the model mis-specification on the mean and dispersion functions in SPF. In addition, this study analyzed the characteristics of errors in the crash reduction factors (CRFs) obtained when the two models are used to estimate the posterior means and variances, which are essentially estimated through the estimated hyper-parameters in the heterogeneous prior distributions. The simulation study results showed that a mis-estimation on the heterogeneous dispersion parameters through the NB model does not affect the coefficient of the mean functions, but the variances of the prior distribution are seriously mis-estimated when the NB model is used to develop SPFs without considering the heterogeneity in dispersion. Consequently, when the NB model is used erroneously to estimate the prior distributions with heterogeneous dispersion parameters, the mis-estimated posterior mean can produce large errors in CRFs up to 120%.

다차원 층화에서 선형계획법을 이용한 표본배정 방법

  • Choe, Jae-Hyeok;NamGung, Pyeong
    • Proceedings of the Korean Statistical Society Conference
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    • 2005.11a
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    • pp.91-96
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    • 2005
  • 다차원층화에서 선형계획법을 이용한 표본배정 방법은 Winkler(1990, 2001), Sitter와 Skinner(1994, 2002)가 제안하였다. 이 방법들은 표본크기가 층 개수보다 크지 않는 경우에 공통적으로 선형계획법을 이용하여 표본배정을 실시하였다. 반복 비율 적합방법(IPF), 일반화 반복 비율 적합(GIFP), SS 방법을 통해 셀 값을 결정하고 선형계획법을 이용하여 표본의 배정확률을 통해 표본배정을 실시한다. 이 3가지 방법들로 표본을 배정하고 평균 및 분산추정량을 비교한다.

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Study on improvement of noise control and SOC estimation using moving average filter and adaptive kalman filter (이동 평균 필터와 적응 칼만 필터를 이용한 노이즈 제어 및 SOC추정 성능 향상 연구)

  • Kim, Gun-Woo;Park, Jin-Hyung;Lee, Seong-Jun;Kim, Jong-Hoon
    • Proceedings of the KIPE Conference
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    • 2019.07a
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    • pp.198-200
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    • 2019
  • 배터리의 상태를 추정하기 위해 전압과 전류 데이터는 사용자가 센서를 통해 얻을 수 있는 정보이며, 이때 노이즈 성분이 포함된 전압 및 전류 데이터는 배터리의 상태 추정을 할 때 정확도를 크게 감소시킬 수 있다. 기존의 확장 칼만필터(EKF, Extended Kalman Filter)를 사용하여 노이즈 성분이 포함된 데이터를 통해 배터리의 상태를 추정했을 때는 노이즈의 영향으로 인해 추정 정확도가 떨어진다. 본 논문은 적응형 칼만 필터(AKF, Adaptive Kalman Filter)를 사용하여 노이즈 분산값을 업데이트 해줌으로써 SOC추정 성능을 향상시켰다. 실험 및 배터리의 모델링은 21700 NMC 고용량 배터리를 사용하였으며, 배터리의 전압에 임의의 노이즈 성분을 추가하여 배터리의 SOC를 추정 정확도를 검증 하였다.

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Estimation of Variance Component on Swine Economic Traits using Multivariate Maternal Animal Model (다변량 모체효과 모형을 이용한 돼지 경제형질의 분산성분 추정)

  • Park, Jong-Won;Kim, Byeong-Woo;Kim, Si-Dong;Jang, Hyeon-Ki;Jeon, Jin-Tae;Kong, Il-Keun;Lee, Jung-Gyu
    • Journal of agriculture & life science
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    • v.44 no.2
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    • pp.29-38
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    • 2010
  • This study looked into estimation of variance component over swine's economic traits by multiple animal model and maternal effect model using on-farm test data of total 31,455 swine of Duroc, Landrace and Yorkshire species that were born between 2000 and 2008. Heritability by estimated additive genetic effect showed higher than one by maternal genetic effect using multivariate maternal animal model in each trait examined by each breed and most heritability when considering only additive genetic effect in multiple traits animal model was estimated to be higher than one by estimated additive genetic effect in multivariate maternal animal model. In correlation between breeding value by estimated maternal genetic effect and phenotypic value using multivariate maternal animal model, rank correlation and simple correlation of breeding value and phenotypic value by maternal genetic effect also showed low positive correlation or strong negative correlation, which can be considered that if correlation with phenotype were increased properly considering maternal genetic effect in each trait by each breed, even better improvement could be promoted.

Hedge Effectiveness in Won-Dollar Futures Markets (원 달러 선물시장을 이용한 헤지효과성)

  • Hong, Chung-Hyo;Moon, Gyu-Hyun
    • The Korean Journal of Financial Management
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    • v.21 no.1
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    • pp.231-253
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    • 2004
  • We examine hedge strategies that use Won-dollar futures to hedge the price risk of the Won-dollar exchange rate. We employ the naive hedge model, minimum variance hedge model and bivariate ECT-ARCH(1) model as hedge instruments, and analyze their hedge performances. The sample period covers from January 2, 2001 to December 31, 2002 with sub-samples such as daily, weekly, bi-weekly prices of the Won-dollar futures and cash. The important findings may be summarized as follows. First, there is no significant difference in hedge ratio between the risk minimum variance model and bivariate ECT-ARCH(1) model that controls for the cointegration relationship of the Won-dollar futures and cash. Second, hedge performance of the naive model and minimum variance model with constant hedge ratios is not far behind that of bivariate ECT-ARCH(1) model with time-varying hedge ratios. This results imply that investors are encouraged to use the minimum variance hedge model to hedge Won-dollar exchange rate with Won-dollar futures. Third, hedge performance and effectiveness of each model is also analyzed with respect to hedge period appear to be greater over long than over the short period. This evidence supports the hypothesis that futures prices would have more time to respond to the greater cash price changes over the longer holding period, leading to an improved hedge performance.

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Analysis on the Correction Factor of Emission Factors and Verification for Fuel Consumption Differences by Road Types and Time Using Real Driving Data (실 주행 자료를 이용한 도로유형·시간대별 연료소모량 차이 검증 및 배출계수 보정 지표 분석)

  • LEE, Kyu Jin;CHOI, Keechoo
    • Journal of Korean Society of Transportation
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    • v.33 no.5
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    • pp.449-460
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    • 2015
  • The reliability of air quality evaluation results for green transportation could be improved by applying correct emission factors. Unlike previous studies, which estimated emission factors that focused on vehicles in laboratory experiments, this study investigates emission factors according to road types and time using real driving data. The real driving data was collected using a Portable Activity Monitoring System (PAMS) according to road types and time, which it compared and analyzed fuel consumption from collected data. The result of the study shows that fuel consumption on national highway is 17.33% higher than the fuel consumption on expressway. In addition, the average fuel consumption of peak time is 4.7% higher than that of non-peak time for 22.5km/h. The difference in fuel consumption for road types and time is verified using ANOCOVA and MANOVA. As a result, the hypothesis of this study - that fuel consumption differs according to road types and time, even if the travel speed is the same - has proved valid. It also suggests correction factor of emission factors by using the difference in fuel consumption. It is highly expected that this study can improve the reliability of emissions from mobile pollution sources.

Application of Approximate FFT Method for Target Detection in Distributed Sensor Network (분산센서망 수중표적 탐지를 위한 근사 FFT 기법의 적용 연구)

  • Choi, Byung-Woong;Ryu, Chang-Soo;Kwon, Bum-Soo;Hong, Sun-Mog;Lee, Kyun-Kyung
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.3
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    • pp.149-153
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    • 2008
  • General underwater target detection methods adopt short-time FFT for estimate target doppler. This paper proposes the efficient target detection method, instead of conventional FFT, using approximate FFT for distributed sensor network target detection, which requires lighter computations. In the proposed method, we decrease computational rate of FFT by the quantization of received signal. For validation of the proposed method, experiment result which is applied to FFT based active sonar detector and real oceanic data is presented.

Bayesian Change Point Analysis for a Sequence of Normal Observations: Application to the Winter Average Temperature in Seoul (정규확률변수 관측치열에 대한 베이지안 변화점 분석 : 서울지역 겨울철 평균기온 자료에의 적용)

  • 김경숙;손영숙
    • The Korean Journal of Applied Statistics
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    • v.17 no.2
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    • pp.281-301
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    • 2004
  • In this paper we consider the change point problem in a sequence of univariate normal observations. We want to know whether there is any change point or not. In case a change point exists, we will identify its change type. Namely, it can be a mean change, a variance change, or both the mean and variance change. The intrinsic Bayes factors of Berger and Pericchi (1996, 1998) are used to find the type of optimal change model. The Gibbs sampling including the Metropolis-Hastings algorithm is used to estimate all the parameters in the change model. These methods are checked via simulation and applied to the winter average temperature data in Seoul.

A Criterion for the Selection of Principal Components in the Robust Principal Component Regression (로버스트주성분회귀에서 최적의 주성분선정을 위한 기준)

  • Kim, Bu-Yong
    • Communications for Statistical Applications and Methods
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    • v.18 no.6
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    • pp.761-770
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    • 2011
  • Robust principal components regression is suggested to deal with both the multicollinearity and outlier problem. A main aspect of the robust principal components regression is the selection of an optimal set of principal components. Instead of the eigenvalue of the sample covariance matrix, a selection criterion is developed based on the condition index of the minimum volume ellipsoid estimator which is highly robust against leverage points. In addition, the least trimmed squares estimation is employed to cope with regression outliers. Monte Carlo simulation results indicate that the proposed criterion is superior to existing ones.

Estimation of Population Mean Using Modified Systematic Sampling and Least Squares Method (변형된 계통추출과 최소제곱법을 이용한 모평균 추정)

  • 김혁주
    • The Korean Journal of Applied Statistics
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    • v.17 no.1
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    • pp.105-117
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    • 2004
  • In this paper, a new method is developed for estimating the mean of a population which has a linear trend. This method involves drawing a sample by the modified systematic sampling, and then estimating the population mean with an adjusted estimator, not with the sample mean itself. We use the method of least squares in determining the adjusted estimator. The proposed method is shown to be more and more efficient as the linear trend becomes stronger. It turns out to be relatively efficient as compared with the conventional methods if $\sigma$$^2$the variance of the random error term in the infinite superpopulation model, is not very large.