• Title/Summary/Keyword: Rosner test

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Impact of Outliers on the Statistical Measures of the Environmental Monitoring Data in Busan Coastal Sea (이상자료가 연안 환경자료의 통계 척도에 미치는 영향)

  • Cho, Hong-Yeon;Lee, Ki-Seop;Ahn, Soon-Mo
    • Ocean and Polar Research
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    • v.38 no.2
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    • pp.149-159
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    • 2016
  • The statistical measures of the coastal environmental data are used in a variety of statistical inferences, hypothesis tests, and data-driven modeling. If the measures are biased, then the statistical estimations and models may also be biased and this potential for bias is great when data contain some outliers defined as extraordinary large or small data values. This study aims to suggest more robust statistical measures as alternatives to more commonly used measures and to assess the performance these robust measures through a quantitative evaluation of more typical measures, such as in terms of locations, spreads, and shapes, with regard to environmental monitoring data in the Busan coastal sea. The detection of outliers within the data was carried out on the basis of Rosner's test. About 5-10% of the nutrient data were found to contain outliers based on Rosner's test. After removal (zero-weighting) of the outliers in the data sets, the relative change ratios of the mean and standard deviation between before and after outlier-removal conditions revealed the figures 13 and 33%, respectively. The variation magnitudes of skewness and kurtosis are 1.36 and 8.11 in a decreasing trend, respectively. On the other hand, the change ratios for more robust measures regarding the mean and standard deviation are 3.7-10.5%, and the variation magnitudes of robust skewness and kurtosis are about only 2-4% of the magnitude of the non-robust measures. The robust measures can be regarded as outlier-resistant statistical measures based on the relatively small changes in the scenarios before and after outlier removal conditions.

Distribution and Trend Analysis of the Significant Wave Heights Using KMA and ECMWF Data Sets in the Coastal Seas, Korea (KMA와 ECMWF 자료를 이용한 연안 유의파고의 분포 및 추세분석)

  • Ko, Dong Hui;Jeong, Shin Taek;Cho, Hong Yeon;Seo, Kyoung Sik
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.29 no.3
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    • pp.129-138
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    • 2017
  • The coastal wave environment is a very important factor that directly affects the change of coastal topography, the habitat of marine life, and the design of offshore structures. In recent years, changes in the wave environment due to climate change are expected, and a trend analysis of the wave environment using available data sets is required. In this paper, significant wave heights which are measured at six ocean buoys (Deokjeokdo, Oeyeondo, Chibaldo, Marado, Pohang, Ullengdo) have been used to analyze long-term trend of normal waves. In advance, the outlier of measured data by Korea Meteorological Administration have been removed using Rosner test. And Pearson correlation analysis between the measured data and ECMWF reanalysis data has been conducted. As a results, correlation coefficient between two data were 0.849~0.938. Meanwhile, Mann-Kendall test has been used to analyze the long-term trend of normal waves. As a results, it was found that there were no trend at Deokjeokdo, Oeyeondo and Chibaldo. However, Marado, Pohang and Ullengdo showed an increasing tendency.

A Covariate-adjusted Logrank Test for Paired Survival Data

  • Jeong, Gyu-Jin
    • Communications for Statistical Applications and Methods
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    • v.9 no.2
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    • pp.533-542
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    • 2002
  • In this paper, a covariate adjusted logrank test is considered for censored paired data under the Cox proportional hazard model. The proposed score test resembles the adjusted logrank test of Tsiatis, Rosner and Tritchler (1985), which is derived from the partial likelihood. The dependence structure for paired data is accommodated into the test statistic by using' sum of square type' variance estimators. Several weight functions are also considered, which produce a class of covariate adjusted weighted logrank tests. Asymptotic normality of the proposed test is established and simulation studies with moderate sample size show the proposed test works well, particularly when there are dependence structure between treatment and covariates.