• 제목/요약/키워드: cumulative distribution functions

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The difference between two distribution functions

  • Hong, Chong Sun
    • Journal of the Korean Data and Information Science Society
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    • 제24권6호
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    • pp.1449-1454
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    • 2013
  • There are many methods for measuring the difference between two location parameters. In this paper, statistics are proposed in order to estimate the difference of two location parameters. The statistics are designed not using the means, variances, signs and ranks, but with the cumulative distribution functions. Hence these are measured as the differences in the area between two univariate cumulative distribution functions. It is found that the difference in the area between two empirical cumulative distribution functions is the difference of two sample means, and its integral is also the difference of two population means.

ROC Curve for Multivariate Random Variables

  • Hong, Chong Sun
    • Communications for Statistical Applications and Methods
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    • 제20권3호
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    • pp.169-174
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    • 2013
  • The ROC curve is drawn with two conditional cumulative distribution functions (or survival functions) of the univariate random variable. In this work, we consider joint cumulative distribution functions of k random variables, and suggest a ROC curve for multivariate random variables. With regard to the values on the line, which passes through two mean vectors of dichotomous states, a joint cumulative distribution function can be regarded as a function of the univariate variable. After this function is modified to satisfy the properties of the cumulative distribution function, a ROC curve might be derived; moreover, some illustrative examples are demonstrated.

On the comparison of cumulative hazard functions

  • Park, Sangun;Ha, Seung Ah
    • Communications for Statistical Applications and Methods
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    • 제26권6호
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    • pp.623-633
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    • 2019
  • This paper proposes two distance measures between two cumulative hazard functions that can be obtained by comparing their difference and ratio, respectively. Then we estimate the measures and present goodness of t test statistics. Since the proposed test statistics are expressed in terms of the cumulative hazard functions, we can easily give more weights on earlier (or later) departures in cumulative hazards if we like to place an emphasis on earlier (or later) departures. We also show that these test statistics present comparable performances with other well-known test statistics based on the empirical distribution function for an exponential null distribution. The proposed test statistic is an omnibus test which is applicable to other lots of distributions than an exponential distribution.

APPROXIMATION TO THE CUMULATIVE NORMAL DISTRIBUTION USING HYPERBOLIC TANGENT BASED FUNCTIONS

  • Yun, Beong-In
    • 대한수학회지
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    • 제46권6호
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    • pp.1267-1276
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    • 2009
  • This paper presents a method for approximation of the standard normal distribution by using hyperbolic tangent based functions. The presented approximate formula for the cumulative distribution depends on one numerical coefficient only, and its accuracy is admissible. Furthermore, in some particular cases, closed forms of inverse formulas are derived. Numerical results of the present method are compared with those of an existing method.

ON GENERALIZED EXTENDED BETA AND HYPERGEOMETRIC FUNCTIONS

  • Shoukat Ali;Naresh Kumar Regar;Subrat Parida
    • 호남수학학술지
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    • 제46권2호
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    • pp.313-334
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    • 2024
  • In the current study, our aim is to define new generalized extended beta and hypergeometric types of functions. Next, we methodically determine several integral representations, Mellin transforms, summation formulas, and recurrence relations. Moreover, we provide log-convexity, Turán type inequality for the generalized extended beta function and differentiation formulas, transformation formulas, differential and difference relations for the generalized extended hypergeometric type functions. Also, we additionally suggest a generating function. Further, we provide the generalized extended beta distribution by making use of the generalized extended beta function as an application to statistics and obtaining variance, coefficient of variation, moment generating function, characteristic function, cumulative distribution function, and cumulative distribution function's complement.

Some applications for the difference of two CDFs

  • Hong, Chong Sun;Son, Yun Hwan
    • Journal of the Korean Data and Information Science Society
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    • 제25권1호
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    • pp.237-244
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    • 2014
  • It is known that the dierence in the length between two location parameters of two random variables is equivalent to the difference in the area between two cumulative distribution functions. In this paper, we suggest two applications by using the difference of distribution functions. The first is that the difference of expectations of a certain function of two continuous random variables such as the differences of two kth moments and two moment generating functions could be defined by using the difference between two univariate distribution functions. The other is that the difference in the volume between two empirical bivariate distribution functions is derived. If their covariance is estimated to be zero, the difference in the volume between two empirical bivariate distribution functions could be defined as the difference in two certain areas.

Bivariate ROC Curve and Optimal Classification Function

  • Hong, C.S.;Jeong, J.A.
    • Communications for Statistical Applications and Methods
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    • 제19권4호
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    • pp.629-638
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    • 2012
  • We propose some methods to obtain optimal thresholds and classification functions by using various cutoff criterion based on the bivariate ROC curve that represents bivariate cumulative distribution functions. The false positive rate and false negative rate are calculated with these classification functions for bivariate normal distributions.

복합재료 피로 수명 분포에 관한 고찰 (Analysis on fatigue life distribution of composite materials)

  • 황운봉;한경섭
    • 대한기계학회논문집
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    • 제12권4호
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    • pp.790-805
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    • 1988
  • 본 연구에서는 유리섬유 강화 에폭시 복합재료의 파괴 강도와 피로 수명을 정 규분포, 로그 정규 분포와 2모수 및 3모수 Weibull 분포 함수의 기대값으로 살펴 보았 다. 2연속 응력 피로 실험 [작은 응력에서 큰 응력으로의 실험(low-high test), 큰 응력에서 작은 응력으로의 실험(high-low test)]의 결과도 분포 함수들을 사용하여 분 석하였다. 비통계학적 누적 손상 법칙들(non-statistical cumulative damage rules) 을 2연속 응력 피로 수명 분산 예측에 이용하기 위해서 동등 순위 가정(equal rank assumption)을 확장하여 수정하였다. 수정한 누적 손상 모형은 Miner의 법칙, Brou- tman과 Sahu의 손상모형 및 Hashin과 Rotem의 모형 등이다.

개수형 자료에 대한 학습곡선효과의 모형화 (Modeling of The Learning-Curve Effects on Count Responses)

  • 최민지;박만식
    • 응용통계연구
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    • 제27권3호
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    • pp.445-459
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    • 2014
  • 일반적으로 특정한 작업에 익숙해진다는 것은 그 작업에 투입되는 노력에 비해 산출되는 성과가 보다 뚜렷해진다는 것을 의미한다. 동일한 양이나 정도의 노력을 들여 특정한 작업을 반복적으로 수행하게 되면 초기 시점보다 원하는 성과를 기대 이상으로 얻게 된다는 것을 의미한다. 이를 학습곡선효과(learning-curve effects)'라고 한다. 본 연구에서는 특정한 작업을 반복시행한 결과가 개수형인 형태로 측정되는 변수에 대해 (역)S자 형태를 가지는 통계적 모형을 적용하고자 한다. 다양한 모의실험 하에서의 모형의 성능을 평가하고 특정질환으로 인한 사망자 자료에 적합하였다.