• Title/Summary/Keyword: nonparametric tests

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Some versatile tests based on percentile tests

  • Park, Hyo-Il;Kim, Ju-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.2
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    • pp.291-296
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    • 2010
  • In this paper, we consider a versatile test based on percentile tests. The versatile test may be useful when the underlying distributions are unknown or quite different types. We consider two kinds of combining functions for the percentile statistics, the quadratic and summing forms and obtain the limiting distributions under the null hypothesis. Then we illustrate our procedure with an example. Finally we discuss some interesting features of the test as concluding remarks.

A Comparison of the Interval Estimations for the Difference in Paired Areas under the ROC Curves (대응표본에서 AUC차이에 대한 신뢰구간 추정에 관한 고찰)

  • Kim, Hee-Young
    • Communications for Statistical Applications and Methods
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    • v.17 no.2
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    • pp.275-292
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    • 2010
  • Receiver operating characteristic(ROC) curves can be used to assess the accuracy of tests measured on ordinal or continuous scales. The most commonly used measure for the overall diagnostic accuracy of diagnostic tests is the area under the ROC curve(AUC). When two ROC curves are constructed based on two tests performed on the same individuals, statistical analysis on differences between AUCs must take into account the correlated nature of the data. This article focuses on confidence interval estimation of the difference between paired AUCs. We compare nonparametric, maximum likelihood, bootstrap and generalized pivotal quantity methods, and conduct a monte carlo simulation to investigate the probability coverage and expected length of the four methods.

A Nonparametric Trend Tests Using TMDL Data in the Nakdong River (낙동강 수계의 수질오염총량 자료를 이용한 비모수적 수질추세 분석)

  • Kim, Mi-Ah;Lee, Soyoung;Mun, Hyunsaing;Cho, Hang-Soo;Lee, Jae-kwan;Kim, Kyunghyun
    • Journal of Korean Society on Water Environment
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    • v.33 no.1
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    • pp.40-50
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    • 2017
  • We were interested in the long-term temporal and spatial variability trends of water quality. Trend tests such as the Seasonal and Regional Kendall tests and LOWESS (LOcally WEighted Scatter plot Smoother) have been recommended as outstanding tools for trend detection. In this study, we conducted four types of nonparametric trend tests (Seasonal and Regional Kendall tests, LOWESS, and flow-adjusted Seasonal Kendall). We aimed to identify water quality trends using the monthly data for five variables (BOD, COD, TN, TP, and flow) collected from 24 sites in the Nakdong River from August 2004 to December 2013. According to the Regional Kendall test, BOD, COD, and TN increased but TP decreased trend. The Seasonal Kendall test showed that BOD, TN, and TP remained constant at 62.5-83.3% of the sites. COD remained constant at 58.3% of the sites. LOWESS showed that TP gradually increased between 2007 and 2008, then decreased slowly at the Gumi, Geumhogang6, Daeam-1 and Milyanggang3 sites. BOD increased slightly between 2008 and 2009, and then decreased slowly at the Namgang4-1 site. Lastly, a flow-adjusted Seasonal Kendall test was conducted. There were different results between Seasonal Kendall and flow-adjusted Seasonal Kendall tests at 11 of the 24 sites. According to the results from six of the eleven sites, BOD increased at one site, showed no trends at three sited, and decreased at two sites. Each of COD, TN increased at two, one site. but TP decreased at two sites.

Comparing the empirical powers of several independence tests in generalized FGM family

  • Zargar, M.;Jabbari, H.;Amini, M.
    • Communications for Statistical Applications and Methods
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    • v.23 no.3
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    • pp.215-230
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    • 2016
  • The powers of some tests for independence hypothesis against positive (negative) quadrant dependence in generalized Farlie-Gumbel-Morgenstern distribution are compared graphically by simulation. Some of these tests are usual linear rank tests of independence. Two other possible rank tests of independence are locally most powerful rank test and a powerful nonparametric test based on the $Cram{\acute{e}}r-von$ Mises statistic. We also evaluate the empirical power of the class of distribution-free tests proposed by Kochar and Gupta (1987) based on the asymptotic distribution of a U-statistic and the test statistic proposed by $G{\ddot{u}}ven$ and Kotz (2008) in generalized Farlie-Gumbel-Morgenstern distribution. Tests of independence are also compared for sample sizes n = 20, 30, 50, empirically. Finally, we apply two examples to illustrate the results.

A Study on Goodness-of-fit Test for Density with Unknown Parameters

  • Hang, Changkon;Lee, Minyoung
    • Communications for Statistical Applications and Methods
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    • v.8 no.2
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    • pp.483-497
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    • 2001
  • When one fits a parametric density function to a data set, it is usually advisable to test the goodness of the postulated model. In this paper we study the nonparametric tests for testing the null hypothesis against general alternatives, when the null hypothesis specifies the density function up to unknown parameters. We modify the test statistic which was proposed by the first author and his colleagues. Asymptotic distribution of the modified statistic is derived and its performance is compared with some other tests through simulation.

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Nonparametric Procedures for Finding the Minimum Effective Dose in Each of Several Group (다중 그룹 상황에서의 최소 효과 용량을 정하는 비모수적 검정법)

  • Bae, Su-Hyun;Kim, Dong-Jae
    • Communications for Statistical Applications and Methods
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    • v.19 no.1
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    • pp.33-45
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    • 2012
  • The primary interest of drug development studies is to estimate the smallest dose that shows a significant difference from the zero-dose control. The smallest dose is called the Minimum Effective dose(MED). In this paper, we suggest a nonparametric procedure to simultaneously find the MED of each group based on placements. The Monte Carlo simulation is adapted to estimate the power and the family-wise error rate(FWE) of the new procedures with those of discussed nonparametric tests to find MED.

Nonparametric Method in One-way Layout for Umbrella Alternatives based on Placement (일원배치법에서 Umbrella Alternatives에 대한 위치를 이용한 비모수 검정법)

  • Lee, Hyejung;Kim, Dongjae
    • The Korean Journal of Applied Statistics
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    • v.28 no.6
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    • pp.1181-1189
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    • 2015
  • The treatment effect in clinical tests depending on dose of the drug; however, it can show a decreasing trend in fixed dose level due to side effects. The trend is known as an umbrella pattern; in addition, the method for the umbrella alternative is quite useful when the tendency is predicted in advance. In this paper, we propose a nonparametric method of umbrella alternatives for a one-way layout by using linear placement described in Orban and Wolfe (1982). The Monte Carlo simulation is adapted to compare the power of proposed procedure with previous methods.

Nonparametric test for ordered alternatives in multifactor designeds (다요인실험계획에서 순서대립가설에 대한 비모수검정법의 연구)

  • 김동희;임동훈
    • The Korean Journal of Applied Statistics
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    • v.3 no.1
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    • pp.11-25
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    • 1990
  • The objective of this paper is to propose a nonparametric distribution-free test for ordered alternatives in k crossed factor designs by using the concepts of combined factor and within-blocks ranks. We investigate the asymptotic normality of the proposed test statistic and the Pitman efficiencies. We also compared the small empirical powers of the tests considered in this paper by Monte Carlo study. Thus we can conclude that the proposed test is efficient and robust for the underlying distribution.

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Nonparametric method in randomized block design for umbrella alternatives based on aligned method and placement (랜덤화 블록 계획법에서 우산형 대립가설에 대한 정렬방법과 위치를 이용한 비모수 검정법)

  • Kim, Jeonghyun;Kim, Dongjae
    • The Korean Journal of Applied Statistics
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    • v.29 no.7
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    • pp.1399-1409
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    • 2016
  • Nonparametric methods in randomized block design were suggested by Friedman (1937) for general alternatives and were also proposed by Page (1963) for ordered alternatives in one-way layout; in addition, K-sample rank tests for umbrella alternatives were suggested by Mack and Wolfe (1981). In this paper, we proposed a nonparametric method of umbrella alternatives for randomized block design using the aligned method proposed by Hodges and Lehmann (1962) to use block information and using placement suggested by Kim (1999). Monte Carlo simulation was also adapted to compare the power of the proposed procedure with previous methods.

Simultaneous Tests with Combining Functions under Normality

  • Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • v.22 no.6
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    • pp.639-646
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    • 2015
  • We propose simultaneous tests for mean and variance under the normality assumption. After formulating the null hypothesis and its alternative, we construct test statistics based on the individual p-values for the partial tests with combining functions and derive the null distributions for the combining functions. We then illustrate our procedure with industrial data and compare the efficiency among the combining functions with individual partial ones by obtaining empirical powers through a simulation study. A discussion then follows on the intersection-union test with a combining function and simultaneous confidence region as a simultaneous inference; in addition, we discuss weighted functions and applications to the statistical quality control. Finally we comment on nonparametric simultaneous tests.