• Title/Summary/Keyword: normality tests

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Nonparametric Test for Used Better Than Aged in Convex Ordering Class(UBAC) of Life Distributions with Hypothesis Testing Applications

  • Abu-Youssef, S.E.
    • International Journal of Reliability and Applications
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    • v.10 no.2
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    • pp.81-88
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    • 2009
  • A non-parametric procedure is presented for testing exponentially against used better than aged in convex ordering class (UBAC) of life distributions based on u-test. Convergence of the proposed statistic to the normal distribution is proved. Selected critical values are tabulated for sample sizes 5(5)40. The Pitman asymptotic relative efficiency of my proposed test to tests of other classes is studied. An example of 40 patients suffering from blood cancer disease demonstrates practical application of the proposed test.

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Rank Tests for Multivariate Linear Models in the Presence of Missing Data

  • Lee, Jae-Won;David M. Reboussin
    • Journal of the Korean Statistical Society
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    • v.26 no.3
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    • pp.319-332
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    • 1997
  • The application of multivariate linear rank statistics to data with item nonresponse is considered. Only a modest extension of the complete data techniques is required when the missing data may be thought of as a random sample, and an appropriate modification of the covariances is derived. A proof of the asymptotic multivariate normality is given. A review of some related results in the literature is presented and applications including longitudinal and repeated measures designs are discussed.

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A Family of Tests for Trend Change in Mean Residual Life with Known Change Point

  • Na, Myung-Hwan;Kim, Jae-Joo
    • Communications for Statistical Applications and Methods
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    • v.7 no.3
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    • pp.789-798
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    • 2000
  • The mean residual function is the expected remaining life of an item at age x. The problem of trend change in the mean residual life is great interest in the reliability and survival analysis. In this paper, we develop a family of test statistics for testing whether or not the mean residual life changes its trend. The asymptotic normality of the test statistics is established. Monte Carlo simulations are conducted to study the performance of our test statistics.

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A Goodness of Fit Approach to Testing Exponential Better than Used (EBU) Life Distributions

  • Abu-Youssef, S.E.
    • International Journal of Reliability and Applications
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    • v.9 no.1
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    • pp.71-78
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    • 2008
  • Based on the goodness of fit approach, a new test is presented for testing exponentiality versus exponential better (worse) than used (EBU (EWU)) class of life distributions. The new test is much simpler to compute, asymptotically normal, enjoys good power and performs better than previous tests in terms of power and Pitman asymptotic efficiencies for several alternatives.

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Testing NBUCA Class of Life Distribution Using U-Test

  • Al-Nachawati, H.
    • International Journal of Reliability and Applications
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    • v.8 no.2
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    • pp.125-135
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    • 2007
  • In this paper, testing exponentiality against new better than used in convex average and denote by (NBUCA), or its dual (NWUCA) is investigated through the U-test. The percentiles of these tests are tabulated for samples sizes n = 5(1)40. The power estimates of the test are simulated for some commonly used distributions in reliability. Pitman's asymptotic efficiency of the test is calculated and compared. Data of 40 patients suffering from blood cancer disease (Leukemia) is considered as a practical application of the proposed test in the medical sciences.

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Topographical measurement of the attachments of the central band of the interosseous membrane on interosseous crests of the radius and ulna

  • Jang, Suk-Hwan;Kim, Kyung-Whan;Jang, Hyo Seok;Kim, Yeong-Seok;Kim, Hojin;Kim, Youngbok
    • Clinics in Shoulder and Elbow
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    • v.24 no.4
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    • pp.253-260
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    • 2021
  • Background: To suggest a reasonable isometric point based on the anatomical consistency of interosseous membrane (IOM) attachment in association with topographic characteristics of the interosseous crests, the footprints of the central band (CB) of the IOM on the radial and ulnar interosseous crests (RIC and UIC) were measured. Methods: We measured the distance from the CB footprints from each apex of both interosseous crests in 14 cadavers and the angles between the forearm axis of rotation (AOR) and the distal slopes of the RIC and UIC in 33 volunteers. Results: The CB footprints lay on the downslope of both interosseous crests with its upper margin on average 3-mm proximal from the RIC's apex consistently in the radial length, showing normality (p>0.05), and on average 16-mm distal from the UIC's apex on the ulna without satisfying normality (p<0.05). The average angle between the UIC's distal slope and the AOR was 1.3°, and the RIC's distal slope to the AOR was 14.0°, satisfying the normality tests (p>0.05), and there was no side-to-side difference in both forearms (p<0.05). Conclusions: The CB attached to the downslope just distal to the RIC's apex constrains the radius to the UIC that coincides with the AOR of the forearm circumduction, maintaining itself both isometrically and isotonically.

Testing the Equality of Several Correlation Coefficients by Permutation Method

  • Um, Yonghwan
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.6
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    • pp.167-174
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    • 2022
  • In this paper we investigate the permutation test for the equality of correlation coefficients in several independent populations. Permutation test is a non-parametric testing methodology based upon the exchangeability of observations. Exchangeability is a generalization of the concept of independent, identically distributed random variables. Using permutation method, we may construct asymptotically exact test. This method is asymptotically as powerful as standard parametric tests and is a valuable tool when the sample sizes are small and normality assumption cannot be met. We first review existing parametric approaches to test the equality of correlation coefficients and compare them with the permutation test. At the end, all the approaches are illustrated using Iris data example.

Nonparametric test on dimensionality of explantory variables (설명변수 차원 축소에 관한 비모수적 검정)

  • 서한손
    • The Korean Journal of Applied Statistics
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    • v.8 no.2
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    • pp.65-75
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    • 1995
  • For the determination of dimension of e.d.r. space, both of Sliced Inverse Regression (SIR) and Principal Hessian Directions (PHD) proposed asymptotic test. But the asymptotic test requires the normality and large samples of explanatory variables. Cook and Weisberg(1991) suggested permutation tests instead. In this study permutation tests are actually made, and the power of them is compared with asymptotic test in the case of SIR and PHD.

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Monitoring of Gene Regulations Using Average Rank in DNA Microarray: Implementation of R

  • Park, Chang-Soon
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.4
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    • pp.1005-1021
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    • 2007
  • Traditional procedures for DNA microarray data analysis are to preprocess and normalize the gene expression data, and then to analyze the normalized data using statistical tests. Drawbacks of the traditional methods are: genuine biological signal may be unwillingly eliminated together with artifacts, the limited number of arrays per gene make statistical tests difficult to use the normality assumption or nonparametric method, and genes are tested independently without consideration of interrelationships among genes. A novel method using average rank in each array is proposed to eliminate such drawbacks. This average rank method monitors differentially regulated genes among genetically different groups and the selected genes are somewhat different from those selected by traditional P-value method. Addition of genes selected by the average rank method to the traditional method will provide better understanding of genetic differences of groups.

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Nonparametric Tests for Detecting Greater Residual Life Times

  • Lim, Jae-Hak;Ibrahim A. Ahmad;Park, Dong-Ho
    • Proceedings of the Korean Reliability Society Conference
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    • 2004.07a
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    • pp.167-175
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    • 2004
  • A nonparametric procedure is proposed to test the exponentiality against the hypothesis that one life distribution has a greater residual life times than the other life distribution. Such a hypothesis turns out to be equivalent to the one that one failure rate is greater than the other and so the proposed test works as a competitor to more IFR tests by Kochar (1979, 1981) and Cheng (1985). Our test statistic utilizes the U-statistics theory and a large sample nonpara metric test is established. The power of the proposed test is discussed by calculating the Pitman asymptotic relative efficiencies against several alter native hypotheses. A numerical example is presented to exemplify the proposed test.

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