• Title/Summary/Keyword: statistical variance

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Methods and Techniques for Variance Component Estimation in Animal Breeding - Review -

  • Lee, C.
    • Asian-Australasian Journal of Animal Sciences
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    • 제13권3호
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    • pp.413-422
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    • 2000
  • In the class of models which include random effects, the variance component estimates are important to obtain accurate predictors and estimators. Variance component estimation is straightforward for balanced data but not for unbalanced data. Since orthogonality among factors is absent in unbalanced data, various methods for variance component estimation are available. REML estimation is the most widely used method in animal breeding because of its attractive statistical properties. Recently, Bayesian approach became feasible through Markov Chain Monte Carlo methods with increasingly powerful computers. Furthermore, advances in variance component estimation with complicated models such as generalized linear mixed models enabled animal breeders to analyze non-normal data.

A Class of Estimators for Population Variance in Two Occasion Rotation Patterns

  • Singh, G.N.;Priyanka, Priyanka;Prasad, Shakti;Singh, Sarjinder;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • 제20권4호
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    • pp.247-257
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    • 2013
  • A variety of practical problems can be addressed in the framework of rotation (successive) sampling. The present work presents a sample rotation pattern where sampling units are drawn on two successive occasions. The problem of estimation of population variance on current (second) occasion in two - occasion successive (rotation) sampling has been considered. A class of estimators has been proposed for population variance that includes many estimators as a particular case. Asymptotic properties of the proposed class of estimators are discussed. The proposed class of estimators is compared with the sample variance estimator when there is no matching from the previous occasion. Optimum replacement policy is discussed. Results are supported with the empirical means of comparison.

Variance components for two-way nested design data

  • Choi, Jaesung
    • Communications for Statistical Applications and Methods
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    • 제25권3호
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    • pp.275-282
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    • 2018
  • This paper discusses the use of projections for the sums of squares in the analyses of variance for two-way nested design data. The model for this data is assumed to only have random effects. Two different sizes of experimental units are required for a given experimental situation, since nesting is assumed to occur both in the treatment structure and in the design structure. So, variance components are coming from the sources of random effects of treatment factors and error terms in different sizes of experimental units. The model for this type of experimental situation is a random effects model with more than one error terms and therefore estimation of variance components are concerned. A projection method is used for the calculation of sums of squares due to random components. Squared distances of projections instead of using the usual reductions in sums of squares that show how to use projections to estimate the variance components associated with the random components in the assumed model. Expectations of quadratic forms are obtained by the Hartley's synthesis as a means of calculation.

Variance Estimation for Imputed Survey Data using Balanced Repeated Replication Method

  • Lee, Jun-Suk;Hong, Tae-Kyong;Namkung, Pyong
    • Communications for Statistical Applications and Methods
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    • 제12권2호
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    • pp.365-379
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    • 2005
  • Balanced Repeated Replication(BRR) is widely used to estimate the variance of linear or nonlinear estimators from complex sampling surveys. Most of survey data sets include imputed missing values and treat the imputed values as observed data. But applying the standard BRR variance estimation formula for imputed data does not produce valid variance estimators. Shao, Chen and Chen(1998) proposed an adjusted BRR method by adjusting the imputed data to produce more accurate variance estimators. In this paper, another adjusted BRR method is proposed with examples of real data.

MS 엑셀 프로그램의 통계분석결과 신뢰성 검증 및 매크로 보완 (분산분석 메뉴를 중심으로) (Test for reliability of MS Excel statistical analysis output and modification of macros (Focused on an Analysis of Variance menu))

  • 김숙영
    • 한국컴퓨터산업학회논문지
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    • 제9권5호
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    • pp.207-216
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    • 2008
  • 초장력 스프레드시트 기능의 엑셀 프로그램에서 자료를 통계적으로 분석하는 데이터분석 메뉴는 엑셀 2000 이후 수정 보완 되고 있지 않으며 그 활용도도 매우 저조하다. 본 연구에서는 엑셀 통계분석 메뉴 활용도 향상을 위하여 사용빈도가 높은 분산분석의 엑셀 메뉴 실행 결과와 계산식에 의한 이론 결과를 비교하고 고차원 분석 매크로를 개발하였다. 실자료를 엑셀 라이터분석 메뉴를 적용하여 얻은 결과와 계산식에 의한 이론 결과는 요인이 한개인 일원배치법이나 두개인 이원배치 법에서 모두 정확히 일치하였다. 즉 엑셀 데이터분석 메뉴의 신뢰성이 검증되었다. 고차원적인 분산분석법인 블록화된 분산분석 결과를 제공하는 매크로 및 일원분산분석법에서 평균 차이 있는 그룹들을 찾아내는 다중비교 분석방법 매크로를 엑셀 함수를 이용하여 개발하였다.

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Note on Properties of Noninformative Priors in the One-Way Random Effect Model

  • Kang, Sang Gil;Kim, Dal Ho;Cho, Jang Sik
    • Communications for Statistical Applications and Methods
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    • 제9권3호
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    • pp.835-844
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    • 2002
  • For the one-way random model when the ratio of the variance components is of interest, Bayesian analysis is often appropriate. In this paper, we develop the noninformative priors for the ratio of the variance components under the balanced one-way random effect model. We reveal that the second order matching prior matches alternative coverage probabilities up to the second order (Mukerjee and Reid, 1999) and is a HPD(Highest Posterior Density) matching prior. It turns out that among all of the reference priors, the only one reference prior (one-at-a-time reference prior) satisfies a second order matching criterion. Finally we show that one-at-a-time reference prior produces confidence sets with expected length shorter than the other reference priors and Cox and Reid (1987) adjustment.

A Bayesian Approach to Detecting Outliers Using Variance-Inflation Model

  • Lee, Sangjeen;Chung, Younshik
    • Communications for Statistical Applications and Methods
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    • 제8권3호
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    • pp.805-814
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    • 2001
  • The problem of 'outliers', observations which look suspicious in some way, has long been one of the most concern in the statistical structure to experimenters and data analysts. We propose a model for outliers problem and also analyze it in linear regression model using a Bayesian approach with the variance-inflation model. We will use Geweke's(1996) ideas which is based on the data augmentation method for detecting outliers in linear regression model. The advantage of the proposed method is to find a subset of data which is most suspicious in the given model by the posterior probability The sampling based approach can be used to allow the complicated Bayesian computation. Finally, our proposed methodology is applied to a simulated and a real data.

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통계적 실험계획 및 분석: Gate Poly-Silicon의 Critical Dimension에 대한 계층적 분산 구성요소 및 웨이퍼 수준 균일성 (Statistical Design of Experiments and Analysis: Hierarchical Variance Components and Wafer-Level Uniformity on Gate Poly-Silicon Critical Dimension)

  • 박성민;김병윤;이정인
    • 대한산업공학회지
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    • 제29권2호
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    • pp.179-189
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    • 2003
  • Gate poly-silicon critical dimension is a prime characteristic of a metal-oxide-semiconductor field effect transistor. It is important to achieve the uniformity of gate poly-silicon critical dimension in order that a semiconductor device has acceptable electrical test characteristics as well as a semiconductor wafer fabrication process has a competitive net-die-per-wafer yield. However, on gate poly-silicon critical dimension, the complexity associated with a semiconductor wafer fabrication process entails hierarchical variance components according to run-to-run, wafer-to-wafer and even die-to-die production unit changes. Specifically, estimates of the hierarchical variance components are required not only for disclosing dominant sources of the variation but also for testing the wafer-level uniformity. In this paper, two experimental designs, a two-stage nested design and a randomized complete block design are considered in order to estimate the hierarchical variance components. Since gate poly-silicon critical dimensions are collected from fixed die positions within wafers, a factor representing die positions can be regarded as fixed in linear statistical models for the designs. In this context, the two-stage nested design also checks the wafer-level uniformity taking all sampled runs into account. In more detail, using variance estimates derived from randomized complete block designs, Duncan's multiple range test examines the wafer-level uniformity for each run. Consequently, a framework presented in this study could provide guidelines to practitioners on estimating the hierarchical variance components and testing the wafer-level uniformity in parallel for any characteristics concerned in semiconductor wafer fabrication processes. Statistical analysis is illustrated for an experimental dataset from a real pilot semiconductor wafer fabrication process.

웨이블릿 계수의 통계적 활동성을 이용한 공간 적응 잡음 제거 (Spatially Adaptive Denoising Using Statistical Activity of Wavelet Coefficients)

  • 엄일규;김유신
    • 한국통신학회논문지
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    • 제28권8C호
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    • pp.795-802
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    • 2003
  • 영상 잡음의 제거를 위해서는 영상에 대한 통계적 모델을 설정하고, 잡음이 섞인 영상에서 원 영상의 분산을 정확하게 추정하는 것이 매우 중요하다. 분산을 추정하기 위해서는 일반적으로 유한한 크기의 주변 영역 정보를 이용한다. 주변 영역의 크기는 평탄 영역 및 에지 영역과 같이 영상의 영역에 따라 달라진다. 즉, 에지 영역인 경우는 주변 영역의 크기를 작게 설정할수록 추정 분산이 보다 정확하며, 평탄 영역의 경우는 주변 영역의 크기가 크면 분산의 추정이 정확해 진다. 이와 같이 추정된 원 영상의 분산을 이용하여 잡음 영상에 Wiener 필터를 적용함으로써 영상의 잡음을 제거하는 것이 일반적이다. 본 논문에서는 영상의 잡음을 제거하기 위해 웨이블릿 영역의 부모-자식 관계를 이용하여 중요도를 작성하고, 이를 이용하여 분산을 구하기 위한 이웃 영역의 범위를 결정하는 방법을 제안한다. 먼저 웨이블릿 계수의 중요한 특성을 획득할 수 있는 중요도를 작성하기 위해 간단한 분류 방법을 사용한다. 중요한 웨이블릿 계수의 수에 근거하여 웨이블릿 계수의 범위를 결정한 뒤 ML 방법을 이용하여 원 신호의 분산을 추정한다. 실험 결과를 통하여 제안 방법이 기존의 방법보다 나은 결과를 보여줌을 알 수 있다.