• Title/Summary/Keyword: error variance

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DETECTION OF OUTLIERS IN WEIGHTED LEAST SQUARES REGRESSION

  • Shon, Bang-Yong;Kim, Guk-Boh
    • Journal of applied mathematics & informatics
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    • v.4 no.2
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    • pp.501-512
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    • 1997
  • In multiple linear regression model we have presupposed assumptions (independence normality variance homogeneity and so on) on error term. When case weights are given because of variance heterogeneity we can estimate efficiently regression parameter using weighted least squares estimator. Unfortunately this estimator is sen-sitive to outliers like ordinary least squares estimator. Thus in this paper we proposed some statistics for detection of outliers in weighted least squares regression.

Asymptotics for realized covariance under market microstructure noise and sampling frequency determination

  • Shin, Dong Wan;Hwang, Eunju
    • Communications for Statistical Applications and Methods
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    • v.23 no.5
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    • pp.411-421
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    • 2016
  • Large frequency limiting distributions of two errors in realized covariance are investigated under noisy and non-synchronous high frequency sampling situations. The first distribution characterizes increased variance of the realized covariance due to noise for large frequency and the second distribution characterizes decreased variance of the realized covariance due to discretization for large frequency. The distribution of the combined error enables us to determine the sampling frequency which depends on a nuisance parameter. A consistent estimator of the nuisance parameter is proposed.

An Efficient Iterative Decoding Stop Criterion using the Variance Value of LLR (LLR의 분산값을 이용한 효율적인 반복중단 알고리즘)

  • 심병섭;정대호;정성태;정경택;김환용
    • Proceedings of the IEEK Conference
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    • 2003.07a
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    • pp.178-181
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    • 2003
  • In this paper, it proposes the efficient iterative decoding stop criterion using the variance value of LLR. It is verifying that the proposal iterative decoding stop criterion can be reduced the average iterative decoding number compared to conventional schemes with a negligible degradation of the error performance.

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A Unit Root Test Based on Bootstrapping

  • Shin, Key-Il;Kang, Hee-Jeong
    • Communications for Statistical Applications and Methods
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    • v.3 no.1
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    • pp.257-265
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    • 1996
  • We consider nonstationary autoregressive autoregressive process with infinite variance of error. In the case of infinite cariance, the limiting distribution of the estimated coefficient is different from that under the finite cariance assumption. In this paper we show that the bootstrap method can be used to approximate the distribution of ordinary least squares estimator of the coefficient in the first order random walk process with infinite variance through some empirical studies and we suggest a test procedure based on bootstrap method for the unit root test.

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A Note on the Asymptotic Property of S2 in Linear Regression Model with Correlated Errors

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.233-237
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    • 2003
  • An asymptotic property of the ordinary least squares estimator of the disturbance variance is considered in the regression model with correlated errors. It is shown that the convergence in probability of S$^2$ is equivalent to the asymptotic unbiasedness. Beyond the assumption on the design matrix or the variance-covariance matrix of disturbances error, the result is quite general and simplify the earlier results.

Estimation on Modified Proportional Hazards Model

  • Lee, Kwang-Ho;Lee, Mi-Sook
    • Journal of the Korean Data and Information Science Society
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    • v.5 no.1
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    • pp.59-66
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    • 1994
  • Heller and Simonoff(1990) compared several methods of estimating the regression coefficient in a modified proportional hazards model, when the response variable is subject to censoring. We give another method of estimating the parameters in the model which also allows the dependent variable to be censored and the error distribution to be unspecified. The proposed method differs from that of Miller(1976) and that of Buckely and James(1979). We also obtain the variance estimator of the coefficient estimator and compare that with the Buckely-James Variance estimator studied by Hillis(1993).

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A Weighted Mean Squared Error Approach to Multiple Response Surface Optimization (다중반응표면 최적화를 위한 가중평균제곱오차)

  • Jeong, In-Jun;Cho, Hyun-Woo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.2
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    • pp.625-633
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    • 2013
  • Multiple response surface optimization (MRSO) aims at finding a setting of input variables which simultaneously optimizes multiple responses. The minimization of mean squared error (MSE), which consists of the squared bias and variance terms, is an effective way to consider the location and dispersion effects of the responses in MRSO. This approach basically assumes that both the terms have an equal weight. However, they need to be weighted differently depending on a problem situation, for example, in case that they are not of the same importance. This paper proposes to use the weighted MSE (WMSE) criterion instead of the MSE criterion in MRSO to consider an unequal weight situation.

An Assessment of Statistical Validity of Articles Published in the Journal of Korean Acupuncture & Moxibusition Society - from 1984 to 2002 - (대한침구학회지 논문의 통계적 오류에 관한 연구)

  • Lee, Seung-deok
    • Journal of Acupuncture Research
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    • v.21 no.1
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    • pp.176-188
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    • 2004
  • This study was carried out to investigate statistical validity of medical articles that used various statistical techniques such as t-test, analysis of variance, correlation analysis, regression analysis and chi-square test. For study 429 original articles using those statistical methods were selected from Journal of Korean Acupuncture & Moxibusition Society published from 1984 to 2002. 429 original articles were reviewed to analyzed the statistical procedures. Results are summarized as follows : 1. In this study 93 articles(21.68%) of 429 ones didn't report statement of statistical method in detail. 2. 53 articles(12.53%) didn't report p-value in correctly, and 245 articles(57.11 %) used mean${\pm}$standard error (Mean${\pm}$SEM.) and 109 articles used mean${\pm}$standard deviation(Mean${\pm}$SD.). All of 23 articles using nonparametric statistical techniques made an error to central tendency or dispersion. 3. 175 articles(59.93%) and 14 articles(4.79%) of 292 ones made an error to description of equal variances and normal distribution. 4. 99 articles(50%) of 185 ones misused t-test and 4 articles of 5 ones misused chi-square test. 5. 28 articles(73.68%) of 38 ones using discrete variable misused parametric technique such as t-test or ANOVA. 2 articles and 1 article of 125 ones choosing paired samples misused independent t-test and Mann-Whitney U test. 6. 20 articles using analysis of variance didn't use multiple comparison.

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Optimal Network Design for the Estimation of Areal Rainfall (면적강우량 산정을 위한 관측망 최적설계 연구)

  • Lee, Jae-Hyeong;Yu, Yang-Gyu
    • Journal of Korea Water Resources Association
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    • v.35 no.2
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    • pp.187-194
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    • 2002
  • To improve the accuracy of the areal rainfall estimates over a river basin, the optimal design method of rainfall network was studied using the stochastic characteristics of measured rainfall data. The objective function was constructed with the estimation error of areal rainfall and observation cost of point rainfall and the observation sites with minimum objective function value were selected as the optimal network. As a stochastic variance estimator, kriging model was selected to minimize the error terms. The annual operation cost including the installation cost was considered as the cost terms and an accuracy equivalent parameter was used to combine the error and cost terms. The optimal design method of rainfall network was studied in the Yongdam dam basin whose raingauge numbers need to be enlarged for the optimal rainfall networks of the basin.

Hydrologic Response Estimation Using Mallows' $C_L$ Statistics (Mallows의 $C_L$ 통계량을 이용한 수문응답 추정)

  • Seong, Gi-Won;Sim, Myeong-Pil
    • Journal of Korea Water Resources Association
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    • v.32 no.4
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    • pp.437-445
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    • 1999
  • The present paper describes the problem of hydrologic response estimation using non-parametric ridge regression method. The method adapted in this work is based on the minimization of the $C_L$ statistics, which is an estimate of the mean square prediction error. For this method, effects of using both the identity matrix and the Laplacian matrix were considered. In addition, we evaluated methods for estimating the error variance of the impulse response. As a result of analyzing synthetic and real data, a good estimation was made when the Laplacian matrix for the weighting matrix and the bias corrected estimate for the error variance were used. The method and procedure presented in present paper will play a robust and effective role on separating hydrologic response.

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