• Title/Summary/Keyword: 최소제곱평균오차

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Estimation of Prediction Values in ARMA Models via the Transformation and Back-Transformation Method (변환-역변환을 통한 자기회귀이동평균모형에서의 예측값 추정)

  • Yeo, In-Kwon;Cho, Hye-Min
    • The Korean Journal of Applied Statistics
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    • v.21 no.3
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    • pp.537-546
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    • 2008
  • One of main goals of time series analysis is to estimate prediction of future values. In this paper, we investigate the bias problem when the transformation and back- transformation approach is applied in ARMA models and introduce a modified smearing estimation to reduce the bias. An empirical study on the returns of KOSDAQ index via Yeo-Johnson transformation was executed to compare the performance of existing methods and proposed methods and showed that proposed approaches provide a bias-reduced estimation of the prediction value.

Recommended Practice for Demand Factor using Regression Analysis Theory depending on Power Consumption Characteristics in Commercial Buildings (업무용빌딩의 전력소비 특성을 고려한 회귀분석이론을 이용한 수용률 기준 설정)

  • Kim, Se-Dong;Shin, Hyo-Seop;Kim, Soo-Gil;Oh, Kie-Bong
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2004.11a
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    • pp.217-222
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    • 2004
  • 고도 정보화 사회의 진전으로 전기에너지의 소비는 급격히 증가하고 있다. 특히 업무용 빌딩과 같은 전력다소비 건물에서는 전력의 효율적 이용에 의한 에너지절감은 물론 설계 단계에서의 합리적인 전기설비 설계가 요청되고 있다. 현재 우리나라의 기후 특성과 전력소비 특성을 고려한 합리적인 전기설비 설계를 위한 기초 자료가 매우 미흡한 실정이다. 본 연구에서는 합리적인 수용률 기준을 설정하기 위하여 사무소용 빌딩의 전력 소비 특성을 조사 분석하였고, 아울러 전기설비설계사무소에서 적용하고 있는 수용률을 조사 분석하였다. 조사된 자료 전체의 특징과 중심적인 경향을 알아내기 위해서 평균값, 중앙값, 표준편차, 최대 값, 최소 값, 회귀모형식, 최소제곱 평균오차 등의 확률 통계적 파라미터들을 수용률 기준 설정을 위한 특징 파라미터로 선택하였다. 그리고, 데이터의 신뢰성을 비교 분석하기 위하여 선형적인 방법과 비선형적인 방법으로 그 경향을 추정하여 곡선으로 나타내었다. 이러한 방법에 의하여 얻어진 분석 자료를 이용하여 적정 변압기 용량 설정을 위하여 데이터베이스화하였고, 변전설비용량의 합리적인 설계를 위하여 수용률 기준 적용시에 필요한 자료로 활용할 수 있으리라 사료된다.

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Comparison of Two Parametric Estimators for the Entropy of the Lognormal Distribution (로그정규분포의 엔트로피에 대한 두 모수적 추정량의 비교)

  • Choi, Byung-Jin
    • Communications for Statistical Applications and Methods
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    • v.18 no.5
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    • pp.625-636
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    • 2011
  • This paper proposes two parametric entropy estimators, the minimum variance unbiased estimator and the maximum likelihood estimator, for the lognormal distribution for a comparison of the properties of the two estimators. The variances of both estimators are derived. The influence of the bias of the maximum likelihood estimator on estimation is analytically revealed. The distributions of the proposed estimators obtained by the delta approximation method are also presented. Performance comparisons are made with the two estimators. The following observations are made from the results. The MSE efficacy of the minimum variance unbiased estimator appears consistently high and increases rapidly as the sample size and variance, n and ${\sigma}^2$, become simultaneously small. To conclude, the minimum variance unbiased estimator outperforms the maximum likelihood estimator.

Procedure for the Selection of Principal Components in Principal Components Regression (주성분회귀분석에서 주성분선정을 위한 새로운 방법)

  • Kim, Bu-Yong;Shin, Myung-Hee
    • The Korean Journal of Applied Statistics
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    • v.23 no.5
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    • pp.967-975
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    • 2010
  • Since the least squares estimation is not appropriate when multicollinearity exists among the regressors of the linear regression model, the principal components regression is used to deal with the multicollinearity problem. This article suggests a new procedure for the selection of suitable principal components. The procedure is based on the condition index instead of the eigenvalue. The principal components corresponding to the indices are removed from the model if any condition indices are larger than the upper limit of the cutoff value. On the other hand, the corresponding principal components are included if any condition indices are smaller than the lower limit. The forward inclusion method is employed to select proper principal components if any condition indices are between the upper limit and the lower limit. The limits are obtained from the linear model which is constructed on the basis of the conjoint analysis. The procedure is evaluated by Monte Carlo simulation in terms of the mean square error of estimator. The simulation results indicate that the proposed procedure is superior to the existing methods.

Scheduling Algorithm for Multiuser MIMO-OFDM System (MMSE-SIC 기반 상향링크 다중 사용자 MIMO-OFDM 시스템에서 공정한 스케줄링 기법)

  • Lee, Pan-Hyung;Lee, Jae-Hong
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2008.11a
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    • pp.91-94
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    • 2008
  • 본 논문에서는 준 정적(quasi-static) 레일레이 페이딩(Rayleigh fading) 채널에서 상향링크 다중 사용자 MIMO-OFDM 시스템을 위한 최소평균제곱오차-순차간섭제거(MMSE-SIC: Minimum mean square error-successive interference cancellation) 수신기에 대해 연구한다. 송신 안테나가 하나인 사용자와 수신 안테나가 다수인 기지국에서 MMSE-SIC 수신기를 기반으로 신호를 검출하는 시스템에서는 하나의 부대역 내에서 동시에 전송 가능한 사용자의 수가 기지국에서의 수신안테나 수보다 작아야 하는 제한 조건을 가지고 있다. 따라서 사용자간 공정성을 보장하고 시스템의 효율성을 높이기 위해 낮은 복잡도를 가지는 비례 공정(Proportional fair) 스케줄링 알고리즘을 제안한다. 제안된 비례 공정 스케줄링 알고리즘에서는 부대역 내에서 다중 사용자 채널 행렬을 기반으로 동시에 전송하는 사용자들의 집합을 찾는다. 평균 채널 이득이 사용자마다 다른 환경에서의 모의실험을 통해 제안된 비례 공정 스케줄링 기법의 성능을 알아본다. 제안된 비례 공정 스케줄링 기법은 기존의 공정성을 기반으로 하는 스케줄링 알고리즘보다 더 큰 일반 비례 공정(General proportional fair) 기준과 더 높은 셀 수율(Cell throughput)을 가지는 것을 보이고 있다.

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Design of the GLR Chart in Integrated Process Control (통합공정관리에서 일반화가능도비 관리도의 설계)

  • Chun, Ga-Young;Lee, Jae-Heon
    • Communications for Statistical Applications and Methods
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    • v.17 no.3
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    • pp.357-365
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    • 2010
  • This paper considers the integrated process control procedure for detecting special causes in an IMA(1,1) noise process that is being adjusted using a minimum mean squared error adjustment. As a SPC procedure, we use a GLR chart for detecting special causes whose effects are the sustained shift or the sustained drift in the process mean, and the sustained shift in the process variance. For the design of the GLR chart, we derive expressions for the control limit which accurately satisfies the given in-control ARL.

Autocorrelation in Statistical Analyses of Fisheries Time Series Data (수산 관련 시계열 자료를 이용한 통계학적 분석에서의 자기상관에 대한 고찰)

  • Park Young Cheol;Hiyama Yoshiaki
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.35 no.3
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    • pp.216-222
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    • 2002
  • Autocorrelation in time series data can affect statistical inference in correlation or regression analyses. To improve a regression model from which the residuals are autocorrelated, Yule-Walker method, nonlinear least squares estimation, maximum likelihood method and 'prewhitening' method have been used to estimate the parameters in a regression equation. This study reviewed on the estimation methods of preventing spurious correlation in the presence of autocorrelation and applied the former three methods, Yule-Walker, nonlinear least squares and maximum likelihood method, to a 20-year real data set. Monte carlo simulation was used to compare the three parameter estimation methods. However, the simulation results showed that the mean squared error distributions from the three methods simulated do not differ significantly.

Precision GPS Orbit Determination and Analysis of Error Characteristics (정밀 GPS 위성궤도 결정 및 오차 특성 분석)

  • Bae, Tae-Suk
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.27 no.4
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    • pp.437-444
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    • 2009
  • A bi-directional, multi-step numerical integrator is developed to determine the GPS (Global Positioning System) orbit based on a dynamic approach, which shows micrometer-level accuracy at GPS altitude. The acceleration due to the planets other than the Moon and the Sun is so small that it is replaced by the empirical forces in the Solar Radiation Pressure (SRP) model. The satellite orbit parameters are estimated with the least-squares adjustment method using both the integrated orbit and the published IGS (International GNSS Service) precise orbit. For this estimation procedure, the integration should be applied to the partial derivatives of the acceleration with respect to the unknown parameters as well as the acceleration itself. The accuracy of the satellite orbit is evaluated by the RMS (Root Mean Squares error) of the residuals calculated from the estimated orbit parameters. The overall RMS of orbit error during March 2009 was 5.2 mm, and there are no specific patterns in the absolute orbit error depending on the satellite types and the directions of coordinate frame. The SRP model used in this study includes only the direct and once-per-revolution terms. Therefore there is errant behavior regarding twice-per-revolution, which needs further investigation.

Search Space Partitioning-based Receiver for Generalized Spatial Modulation under Channel Information Errors (일반화 공간변조 시스템에서 채널 정보 오차를 고려한 탐색 영역 분할 수신기)

  • Yoon, Hakjoon;Im, Changyong;Lee, Kyungchun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.12
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    • pp.1631-1637
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    • 2019
  • In this paper, we propose a low-complexity robust maximum likelihood (ML) receiver for generalized spatial modulation. The proposed receiver performs the transmit antenna partition to lower the computational loads. After we divide the transmit antenna combinations into two parts, one of which is "the likely TAC part," and the other of which is "the unlikely TAC part", based on the minimum mean square error (MMSE) filtering output. We first perform the maximum likelihood detection only in the likely TAC part. Then we evaluate the reliability of the solution found in the first search, and based its reliability we decide whether we continue the search in the unlikely TAC part. This partitioned search strategy maintains the performance of the conventional robust maximum likelihood receiver and simultaneously lowers computational loads. Through simulation, we found that our newly-proposed receiver achieves considerable gains over the conventional robust ML detector in terms of the computational loads while providing almost the same performance.

Derivation of Asymptotic Formulas for the Signal-to-Noise Ratio of Mismatched Optimal Laplacian Quantizers (불일치된 최적 라플라스 양자기의 신호대잡음비 점근식의 유도)

  • Na, Sang-Sin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.5C
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    • pp.413-421
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    • 2008
  • The paper derives asymptotic formulas for the MSE distortion and the signal-to-noise ratio of a mismatched fixed-rate minimum MSE Laplacian quantizer. These closed-form formulas are expressed in terms of the number N of quantization points, the mean displacement $\mu$, and the ratio $\rho$ of the standard deviation of the source to that for which the quantizer is optimally designed. Numerical results show that the principal formula is accurate in that, for rate R=$log_2N{\geq}6$, it predicts signal-to-noise ratios within 1% of the true values for a wide range of $\mu$, and $\rho$. The new findings herein include the fact that, for heavy variance mismatch of ${\rho}>3/2$, the signal-to-noise ratio increases at the rate of $9/\rho$ dB/bit, which is slower than the usual 6 dB/bit, and the fact that an optimal uniform quantizer, though optimally designed, is slightly more than critically mismatched to the source. It is also found that signal-to-noise ratio loss due to $\mu$ is moderate. The derived formulas can be useful in quantization of speech or music signals, which are modeled well as Laplacian sources and have changing short-term variances.