• 제목/요약/키워드: normality

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An Improved Quantize-Quantize Plot for Normality Test

  • Lee, Jea-Young;Rhee, Seong-Won
    • Communications for Statistical Applications and Methods
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    • 제5권1호
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    • pp.67-75
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    • 1998
  • A new graphical method, named transformed quantize-quantile (TQQ), of a quantize-quantile (Q-Q) Plot is developed for the detection of deviations from the normal distribution. It will be shown that TQQ is helpful for detecting patterns of how points depart from normality. TQQ characteristics of the various kinds of representations are illustrated by a generated sample from a composite of a normal distribution and a clinical example for TQQ is constructed and explained.

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NONLINEAR ASYMMETRIC LEAST SQUARES ESTIMATORS

  • Park, Seung-Hoe;Kim, Hae-Kyung;Lee, Young
    • Journal of the Korean Statistical Society
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    • 제32권1호
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    • pp.47-64
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    • 2003
  • In this paper, we consider the asymptotic properties of asymmetric least squares estimators for nonlinear regression models. This paper provides sufficient conditions for strong consistency and asymptotic normality of the proposed estimators and derives asymptotic relative efficiency of the pro-posed estimators to the regression quantile estimators. We give some examples and results of a Monte Carlo simulation to compare the asymmetric least squares estimators with the regression quantile estimators.

Test of Normality Based on the Transformed Lorenz Curve

  • Kang, Suk-Bok;Cho, Young-Suk
    • Communications for Statistical Applications and Methods
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    • 제6권3호
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    • pp.901-908
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    • 1999
  • Using the Transformed Lorenz curve which is introduced by Cho et al.(1999) we propose the test statistic for testing of normality that is very important test in statistical analysis and compare the proposed test statistic with the Shapiro and Wilk's W test statistic in terms of the power of test through by Monte Carlo method.

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Minimax Choice and Convex Combinations of Generalized Pickands Estimator of the Extreme Value Index

  • Yun, Seokhoon
    • Journal of the Korean Statistical Society
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    • 제31권3호
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    • pp.315-328
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    • 2002
  • As an extension of the well-known Pickands (1975) estimate. for the extreme value index, Yun (2002) introduced a generalized Pickands estimator. This paper searches for a minimax estimator in the sense of minimizing the maximum asymptotic relative efficiency of the Pickands estimator with respect to the generalized one. To reduce the asymptotic variance of the resulting estimator, convex combinations of the minimax estimator are also considered and their asymptotic normality is established. Finally, the optimal combination is determined and proves to be superior to the generalized Pickands estimator.

Sequential Estimation with $\beta$-Protection of the Difference of Two Normal Means When an Imprecision Function Is Variable

  • Kim, Sung-Lai;Kim, Sung-Kyun
    • Journal of the Korean Statistical Society
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    • 제31권3호
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    • pp.379-389
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    • 2002
  • For two normal distribution with unknown means and unknown variances, a sequential procedure for estimating the difference of two normal means which satisfies both the coverage probability condition and the $\beta$-protection is proposed under some smoothness of variable imprecision function, and the asymptotic normality of the proposed stopping time after some centering and scaling is given.

NORMALITY CRITERIA FOR A FAMILY OF HOLOMORPHIC FUNCTIONS CONCERNING THE TOTAL DERIVATIVE IN SEVERAL COMPLEX VARIABLES

  • Cao, Tingbin;Liu, Zhixue
    • 대한수학회지
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    • 제53권6호
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    • pp.1391-1409
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    • 2016
  • In this paper, we investigate a family of holomorphic functions in several complex variables concerning the total derivative (or called radial derivative), and obtain some well-known normality criteria such as the Miranda's theorem, the Marty's theorem and results on the Hayman's conjectures in several complex variables. A high-dimension version of the famous Zalcman's lemma for normal families is also given.

Local Asymptotic Normality for Independent Not Identically Distributed Observations in Semiparametric Models

  • Park, Byeong U.;Jeon, Jong W.;Song, Moon S.;Kim, Woo C.
    • Journal of the Korean Statistical Society
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    • 제20권1호
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    • pp.85-92
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    • 1991
  • A set of conditions ensuring local asymptotic normality for independent but not necessarily identically distributed observations in semiparametric models is presented here. The conditions are turned out to be more direct and easier to verify than those of Oosterhoff and van Zwet(1979) in semiparametric models. Examples considered include the simple linear regression model and Cox's proportional hazards model without censoring where the covariates are not random.

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일변량 공간 연관성 측도의 통계적 검정을 위한 일반화된 고차 적률 추출 절차: 정규성 가정의 경우 (A Generalized Procedure to Extract Higher Order Moments of Univariate Spatial Association Measures for Statistical Testing under the Normality Assumption)

  • 이상일
    • 대한지리학회지
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    • 제43권2호
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    • pp.253-262
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    • 2008
  • 이 논문의 주요 목적은 정규성 가정 하에 일변량 공간 연관성 측도의 첫 번째 네 적률을 구해내는 일반화된 추출 절차를 정식화하고, 그것을 바탕으로 각 측도의 가설 검정을 위해 정규근사가 갖는 가능성과 한계를 평가하는 것이다. 중요 연구 결과는 다음과 같다. 첫째, 이전의 연구에 기반함으로써, 정규성 가정 하에 전역적 측도와 국지적 측도에 모두 적용될 수 있는 일반화된 적률 추출절차가 도출되었다. 개별 공간 연관성 측도를 위한 필수적인 메트릭스가 적절히 정의되었을 때, 일반화된 유의성 검정 방법은 각 공간 연관성 측도의 기대값과 분산은 물론 첨도와 왜도를 효과적으로 산출하였다. 둘째, 첫 번째 두 적률에 근거한 정규근사 방법은 전역적 통계량에 대해서는 유효한 것으로 판명되었지만, 국지적 통계량에 대해서는 매우 높은 왜도와 첨도로 말미암아 그 유효성이 현저히 떨어지는 것으로 드러났다.

임의중도절단자료에 대한 로그정규성 검정 (Testing Log Normality for Randomly Censored Data)

  • 김남현
    • 응용통계연구
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    • 제24권5호
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    • pp.883-891
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    • 2011
  • 수명시간에 대한 모형으로 로그정규분포가 자주 사용되며, 이는 자료의 변환에 의하여 정규성 검정과 동일한 문제로 생각할 수 있다. 따라서 자료의 로그정규성 검정을 위하여, 정규성 검정에 자주 이용되는 Shapiro-Wilk 형태의 검정통계량을 Kaplan-Meier의 product limit 경험분포함수를 이용하여 임의중도절단자료로 일반화한다. Cram er von Mises 통계량을 임의중도절단자료로 일반화한 Koziol과 Green (1976)의 통계량과 비교하였으며 이를 위하여 단순귀무가설을 가정하였다. 중도절단분포에 대한 모형으로는 Koziol과 Green (1976)에서 제시한 모형과 이와 유사한 다른 모형 두 가지를 고려하였다. 검정력 비교 결과 제시한 통계량이 로그정규성 또는 정규성 검정에 더 좋은 검정력을 보여주었으며 검정력은 중도절단분포 모형보다는 자료의 중도절단비율에 영향을 받는다는 것을 볼 수 있었다.

탐진강 수질측정 지점 간 동질성 검정을 위한 비모수적 자료 분석 (A Non-parametric Analysis of the Tam-Jin River : Data Homogeneity between Monitoring Stations)

  • 김미아;이수웅;이재관;이정섭
    • 한국물환경학회지
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    • 제21권6호
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    • pp.651-658
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    • 2005
  • The Non-parametric Analysis is powerful in data test especially for the non- normality water quality data. The data at three monitoring stations of the Tam-Jin River were evaluated for their normality using Skewness, Q-Q plot and Shapiro-Willks tests. Various constituent of water quality data including temperature, pH, DO, SS, BOD, COD, TN and TP in the period of January 1994 to December 2004 were used as dataset. Shapiro-Willks normality test was carried out for a test 5% significance level. Most water quality data except DO at monitoring stations 1 and 2 showed that data does not normally distributed. It is indicating that non-parametric method must be used for a water quality data. Therefore, a homogeneity was conducted by Mann-Whitney U test (p<0.05). Two stations were paired in three pairs of such stations. Differences between stations 1, 2 and stations 1, 3 for pH, BOD, COD, TN and TP were meaningful, but Tam-Jin 2 and 3 stations did not meaningful. In addition, a narrow gap of the water quality ranges is not a difference. Categories in which all three pairs of stations (1 and 2, 2 and 3, 1 and 3) in the Tam-Jin River showed difference in water quality were analyzed on TN and TP. The results of in this research suggest a right analysis in the homogeneity test of water quality data and a reasonable management of pollutant sources.