• 제목/요약/키워드: Cumulative Distribution Function

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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.

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.

Noncentral F-Distribution for an M-ary Phase Shift Keying Wedge-Shaped Region

  • Kim, Jung-Su;Chong, Jong-Wha
    • ETRI Journal
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    • 제31권3호
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    • pp.345-347
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    • 2009
  • This letter presents an alternative analytical expression for computing the probability of an M-ary phase shift keying (MPSK) wedge-shaped region in an additive white Gaussian noise channel. The expression is represented by the cumulative distribution function of known noncentral F-distribution. Computer simulation results demonstrate the validity of our analytical expression for the exact computation of the symbol error probability of an MPSK system with phase error.

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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.

Weibull형 고장분포를 갖는 선박용 부품의 최적 보전시기의 결정수법에 관한 연구 (A Study on the Decision of an Optimal Maintenance Period for Ship's Machinery Items using the Cumulative Hazard Rate Function for Weibull Distribution)

  • 유희한
    • Journal of Advanced Marine Engineering and Technology
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    • 제24권2호
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    • pp.90-96
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    • 2000
  • The technology of preventive maintenance and corrective maintenance is widely applied to ships in order to maintain the good voyageable condition. One of the most important fields of marine engineering is to seek the maximum availability and to solve the stochastic maintenance problem such that the cost for corrective maintenance is minimized. Accordingly, for the purpose of making the most suitable maintenance schedule which minimizes the expected cost function, this paper suggests the method to grasp the failure characteristics by the ship's maintenance data that are collected from the past. And, suggests the method to estimate the optimal maintenance interval by using the dynamic programming and the cumulative hazard rate function attained from the maintenance data.

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An importance sampling for a function of a multivariate random variable

  • Jae-Yeol Park;Hee-Geon Kang;Sunggon Kim
    • Communications for Statistical Applications and Methods
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    • 제31권1호
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    • pp.65-85
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    • 2024
  • The tail probability of a function of a multivariate random variable is not easy to estimate by the crude Monte Carlo simulation. When the occurrence of the function value over a threshold is rare, the accurate estimation of the corresponding probability requires a huge number of samples. When the explicit form of the cumulative distribution function of each component of the variable is known, the inverse transform likelihood ratio method is directly applicable scheme to estimate the tail probability efficiently. The method is a type of the importance sampling and its efficiency depends on the selection of the importance sampling distribution. When the cumulative distribution of the multivariate random variable is represented by a copula and its marginal distributions, we develop an iterative algorithm to find the optimal importance sampling distribution, and show the convergence of the algorithm. The performance of the proposed scheme is compared with the crude Monte Carlo simulation numerically.

고속도로 통행량 예측을 위한 새로운 동적 알고리즘 (A New Dynamic Prediction Algorithm for Highway Traffic Rate)

  • 이광연;박기섭
    • 한국시뮬레이션학회논문지
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    • 제29권3호
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    • pp.41-48
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    • 2020
  • 본 논문에서는 고속도로 통행량을 보다 정확하게 예측하기 위한 새로운 방법으로 통행량에 대한 누적분포함수를 이용한 동적 예측 알고리즘을 제시한다. 여기서 누적분포함수의 근사함수를 수치적 방법인 내츄럴 큐빅 스플라인(natural cubic spline) 보간법과 레벤버그-마쿼트(Levenberg-Marquardt) 방법을 통해 얻는다. 이 알고리즘은 금융수학에서 활용하는 누적 분포함수를 이용한 난수 생성 알고리즘을 통행량 예측에 알맞도록 새롭게 구조화한 것이다. 이 알고리즘으로 고속도로 통행량을 시뮬레이션하면 실제 통행량과 매우 흡사한 결과를 얻을 수 있음을 확인할 수 있다. 따라서 이 알고리즘은 고속도로뿐만 아니라 통행량 예측이 필요한 다양한 분야에서 활용할 수 있는 새로운 알고리즘이다.

Nonparametric Inference for the Recurrent Event Data with Incomplete Observation Gaps

  • Kim, Jin-Heum;Nam, Chung-Mo;Kim, Yang-Jin
    • 응용통계연구
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    • 제25권4호
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    • pp.621-632
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    • 2012
  • Recurrent event data can be easily found in longitudinal studies such as clinical trials, reliability fields, and the social sciences; however, there are a few observations that disappear temporarily in sight during the follow-up and then suddenly reappear without notice like the Young Traffic Offenders Program(YTOP) data collected by Farmer et al. (2000). In this article we focused on inference for a cumulative mean function of the recurrent event data with these incomplete observation gaps. Defining a corresponding risk set would be easily accomplished if we know the exact intervals where the observation gaps occur. However, when they are incomplete (if their starting times are known but their terminating times are unknown) we need to estimate a distribution function for the terminating times of the observation gaps. To accomplish this, we treated them as interval-censored and then estimated their distribution using the EM algorithm proposed by Turnbull (1976). We proposed a nonparametric estimator for the cumulative mean function and also a nonparametric test to compare the cumulative mean functions of two groups. Through simulation we investigated the finite-sample performance of the proposed estimator and proposed test. Finally, we applied the proposed methods to YTOP data.