• 한국수학사학회지
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• 제11권2호
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• pp.63-76
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• 1998

When teaching the linear regression analysis in the class, the power transformation must be introduced to fit the linear regression model for nonlinear data. Box and Cox (1964) proposed the attractive power transformation technique which is so called Box-Cox transformation. In this paper, an effective algorithm selecting an appropriate value for Box-Cox transformation is developed which is considered to find a value minimizing error sum of squares. When the proposed algorithm is used to find a value for transformation, the number of iterations needs to be considered. Thus, the number of iterations is examined through simulation study. Since SAS is one of most widely used packages and does not provide the procedure that performs iterative Box-Cox transformation, a SAS program automatically choosing the value for transformation is developed. Hence, the students could learn how the Box-Cox transformation works, moreover, researchers can use this for analysis of data.

• 한국농공학회지
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• 제32권E호
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• pp.20-32
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• 1990

Abstract This study was conducted to pursue the normalization of frequency distribution by making an approach to the coefficient of skewness to nearly zero through the Box-Cox transformation, to get probable flood flows can be calculated by means of the transformation equation which has been derivated by Box-Cox transformation in the annual maximum series of the applied watersheds. It has been concluded that Box-Cox transfromation is proved to be more efficient than logarithmic, square root and SMEMAX transformation which is based on the trigonometric solution of a right triangle whose three verteces repesent the smallest, median and largest observed values of a population in making the coefficient of skewness nearer to zero. Consequently it is shown that probable flood flows according to the return period based on Box-Cox transformation are closer to the observed data as compared to other methods including SMEMAX transformation and fitted probability distributions such as the three parameter lognormal and the type I extremal distribution for the applied watersheds.

• Journal of the Korean Statistical Society
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• 제34권3호
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• pp.173-183
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• 2005

The Box-Cox power transformation is generally used for variance stabilization. Recently, Shin and Kang (2001) showed, under the Box-Cox transformation, invariant properties to the original model under the large mean and relatively small variance assumptions in time series analysis. In this paper we obtain some invariant properties in spatial statistics. Spatial statistics, Invariant Property, Variogram, Box-Cox power Transformation.

• 응용통계연구
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• 제14권1호
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• pp.137-148
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• 2001

비율을 나타내는 요소들로 이루어진 구성비율자료는 각 행들의 합이 1이 되는 제약을 가지고 있어 통계적으로 다루기가 쉽지 않다. 더구나 자료의 구조가 선형적인 형태를 보이지 않는 특성을 가지기 때문에 주성분분석과 같은 선형적인 다변량기법들을 구성비율자료에 적용을 할 때 잘못된 해석과 추론이 이루어질 가능성이 있다. 본 논문에서는 구성비율자료의 주성분분석에서 기존의 방법들이 가지는 문제점을 해결하기 위해 Box-Cox 대비변환(Box-Cox contrast transformation)을 이용한 새로운 형태의 분석방법을 제시한다. 그리고 실제자료의 분석과 모의실험을 통해서 Aitchison(1983)이 제시한 방법과 수행능력을 비교하고자 한다.

• Journal of applied mathematics & informatics
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• 제22권1_2호
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• pp.541-547
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• 2006

A procedure for investigating the influence of observations in choosing Box-Cox transformation for multivariate data is suggested. It is effective in spotting influential observations. A numerical example is provided for illustration.

• 한국수자원학회논문집
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• 제36권2호
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• pp.153-159
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• 2003

I-D-F곡선을 유도할 때 강우자료의 보유연한이 충분하지 않을 경우 지속시간별 강우강도의 변화가 매끄럽게 연결되지 못하는 경우가 발생하기도 한다. 특히 곡선에서, 상대적인 장시간에 강우강도가 크게 되는 문제는 실무적으로 I-D-F 곡선을 이용하는데 큰 혼란을 야기 시킨다. 본 연구에서는 강우자료를 Box-Cox변환을 이용하여 지속시간과 강우강도의 상관관계를 통해 이러한 문제를 해결하는 방법을 제시한다. 산청과 영천의 강우자료에 대한 분석결과 Box-Cox 변환의 실효성을 확인할 수 있었다.

• Journal of the Korean Data and Information Science Society
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• 제15권2호
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• pp.413-422
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• 2004

Box-Cox power transformation is employed for analyzing volatilities in Korean financial time series such as KOSPI, KOSDAQ index and interest rates. Statistical procedures for Box-Cox transformed ARCH models are presented. For illustration, diverse financial time series data are analyzed and appropriate power transformations are suggested for each data.

• Communications for Statistical Applications and Methods
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• 제11권1호
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• pp.189-196
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• 2004

The sensitivity of the multivariate Box-Cox transformation model to simultaneous perturbations of all the data based on the likelihood displacement is studied in order to detect outliers. An example is given for illustration.

• Journal of the Korean Data and Information Science Society
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• 제22권5호
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• pp.967-976
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• 2011

The Box-Cox transformation is a well known family of power transformations that brings a set of data into agreement with the normality assumption of the residuals and hence the response variable of a postulated model in regression analysis. Normalization (studentization) of the regressors is a common practice in analyzing microarray data. Here, we implement Box-Cox transformation in normalizing regressors in microarray data. Pridictabilty of the model can be improved using data transformation compared to studentization.

• 응용통계연구
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• 제19권2호
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• pp.283-290
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• 2006

일반적으로 Box-Cox변환과 같은 류의 멱변환은 분산 안정화 혹은 분포의 대칭성 향상 등을 목적으로 사용된다. 그러나 원 자료의 평균의 크기가 크면서 분산이 상대 적으로 작은 경우, 즉 변동계수가 작은 경우에는 제대로 작동하지 않는 것이 알려져 있다. 본 논문에서는 이러한 문제점을 해결하기 위한 이동-멱변환을 제안하고 모의실험과 실제 자료 분석을 통하여 그 효과를 확인하였다.