• Title, Summary, Keyword: distribution of supremum

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Genetic association tests when a nuisance parameter is not identifiable under no association

  • Kim, Wonkuk;Kim, Yeong-Hwa
    • Communications for Statistical Applications and Methods
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    • v.24 no.6
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    • pp.663-671
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    • 2017
  • Some genetic association tests include an unidentifiable nuisance parameter under the null hypothesis of no association. When the mode of inheritance (MOI) is not specified in a case-control design, the Cochran-Armitage (CA) trend test contains an unidentifiable nuisance parameter. The transmission disequilibrium test (TDT) in a family-based association study that includes the unaffected also contains an unidentifiable nuisance parameter. The hypothesis tests that include an unidentifiable nuisance parameter are typically performed by taking a supremum of the CA tests or TDT over reasonable values of the parameter. The p-values of the supremum test statistics cannot be obtained by a normal or chi-square distribution. A common method is to use a Davies's upper bound of the p-value instead of an exact asymptotic p-value. In this paper, we provide a unified sine-cosine process expression of the CA trend test that does not specify the MOI and the TDT that includes the unaffected. We also present a closed form expression of the exact asymptotic formulas to calculate the p-values of the supremum tests when the score function can be written as a linear form in an unidentifiable parameter. We illustrate how to use the derived formulas using a pharmacogenetics case-control dataset and an attention deficit hyperactivity disorder family-based example.

CONVERGENCE RATE OF EXTREMES FOR THE GENERALIZED SHORT-TAILED SYMMETRIC DISTRIBUTION

  • Lin, Fuming;Peng, Zuoxiang;Yu, Kaizhi
    • Bulletin of the Korean Mathematical Society
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    • v.53 no.5
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    • pp.1549-1566
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    • 2016
  • Denote $M_n$ the maximum of n independent and identically distributed variables from the generalized short-tailed symmetric distribution. This paper shows the pointwise convergence rate of the distribution of $M_n$ to exp($\exp(-e^{-x})$) and the supremum-metric-based convergence rate as well.

The Limit Distribution of an Invariant Test Statistic for Multivariate Normality

  • Kim Namhyun
    • Communications for Statistical Applications and Methods
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    • v.12 no.1
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    • pp.71-86
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    • 2005
  • Testing for normality has always been an important part of statistical methodology. In this paper a test statistic for multivariate normality is proposed. The underlying idea is to investigate all the possible linear combinations that reduce to the standard normal distribution under the null hypothesis and compare the order statistics of them with the theoretical normal quantiles. The suggested statistic is invariant with respect to nonsingular matrix multiplication and vector addition. We show that the limit distribution of an approximation to the suggested statistic is representable as the supremum over an index set of the integral of a suitable Gaussian process.

The Limit Distribution and Power of a Test for Bivariate Normality

  • Kim, Namhyun
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.187-196
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    • 2002
  • Testing for normality has always been a center of practical and theoretical interest in statistical research. In this paper a test statistic for bivariate normality is proposed. The underlying idea is to investigate all the possible linear combinations that reduce to the standard normal distribution under the null hypothesis and compare the order statistics of them with the theoretical normal quantiles. The suggested statistic is invariant with respect to nonsingular matrix multiplication and vector addition. We show that the limit distribution of an approximation to the suggested statistic is represented as the supremum over an index set of the integral of a suitable Gaussian Process. We also simulate the null distribution of the statistic and give some critical values of the distribution and power results.

REFLECTION PRINCIPLES FOR GENERAL WIENER FUNCTION SPACES

  • Pierce, Ian;Skoug, David
    • Journal of the Korean Mathematical Society
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    • v.50 no.3
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    • pp.607-625
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    • 2013
  • It is well-known that the ordinary single-parameter Wiener space exhibits a reflection principle. In this paper we establish a reflection principle for a generalized one-parameter Wiener space and apply it to the integration of a class of functionals on this space. We also discuss several notions of a reflection principle for the two-parameter Wiener space, and explore whether these actually hold.