• Journal of the Korean Data and Information Science Society
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• 제19권2호
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• pp.635-644
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• 2008

We consider estimation of reliability P(Y

• East Asian mathematical journal
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• 제39권3호
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• pp.331-347
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• 2023

We present an identity on moments of a compound random variable by using an auxiliary counting random variable. Based on this identity, we develop a new recurrence formula for obtaining the raw and central moments of any order for a given compound random variable.

• East Asian mathematical journal
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• 제34권1호
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• pp.59-67
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• 2018

We present new recurrence formulas for the raw and central moments of a compound binomial random variable. Our approach involves relating two compound binomial random variables that have parameters with a difference of 1 for the number of trials, but which have the same parameters for the success probability for each trial. As a consequence of our recursions, the raw and central moments of a binomial random variable are obtained in a recursive manner without the use of Stirling numbers.

• 대한수학회지
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• 제51권3호
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• pp.527-543
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• 2014

The theory of random variable structures was first studied by Ben Yaacov in [2]. Ben Yaacov's axiomatization of the theory of random variable structures used an early result on the completeness theorem for Lukasiewicz's [0, 1]-valued propositional logic. In this paper, we give an elementary approach to axiomatizing the theory of random variable structures. Only well-known results from probability theory are required here.

• Journal of the Korean Data and Information Science Society
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• 제18권3호
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• pp.783-792
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• 2007

We consider estimation of reliability P(Y

• Communications for Statistical Applications and Methods
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• 제15권3호
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• pp.325-332
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• 2008

We consider estimation of reliability P(Y < X) and distribution of the ratio when X and Y are independent uniform random variable and power function random variable, respectively and also consider the estimation problem when X and Y are independent uniform random variable and a half-normal random variable, respectively.

• 대한수학교육학회지:학교수학
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• 제16권1호
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• pp.19-37
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• 2014

현대사회는 대량 정보들을 수집하고 활용하는 정보화 사회로 현대인들에게 통계적 소양이 요구된다. 이에 따라 학교수학에서 통계적 소양의 중요성이 점차 강조되고 있으며, 현직교사나 예비교사들에 대한 통계적 소양 능력의 함양 및 지도 능력 향상이 요구되고 있다. 한편 확률변수는 통계 학습에서 가장 기초적인 개념으로 통계량을 다룰 때에 확률변수를 정의하는 과정으로부터 시작된다. 이에 본 연구에서는 고등학교 통계 영역의 기본 개념인 확률변수 개념에 대한 예비교사들의 이해 정도를 탐색해 보고자 하였다. 이를 위하여 우선적으로, 본 연구의 핵심 내용인 확률변수 개념의 이해도를 보다 정확하게 파악하기 위하여 학문적 측면에서의 정의, 상황에서 드러나는 확률변수의 의미, 그리고 현행(2007 개정) 고등학교 교과서에서의 정의 측면으로 구분하여 재탐색, 정리하고자 하였다. 이를 기반으로, 예비교사 대상의 확률변수 개념의 이해 정도를 조사하기 위한 설문 문항을 마련하였으며, 이를 통해 예비교사들의 확률변수에 대한 이해 정도를 조사하여 분석하였다. 이를 토대로 확률변수 개념 및 전반적인 통계 개념에 대한 교수-학습에 대한 시사점을 제시하고자 하였다.

• Journal of the Korean Data and Information Science Society
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• 제19권3호
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• pp.967-977
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• 2008

We consider densities of quotient Y/X and ratio X/(X+Y), and estimation of reliability P(Y

• Communications for Statistical Applications and Methods
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• 제27권3호
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• pp.285-299
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• 2020

In many cases, we are interested in identifying independence between variables. For continuous random variables, correlation coefficients are often used to describe the relationship between variables; however, correlation does not imply independence. For finite discrete random variables, we can use the Pearson chi-square test to find independency. For the mixed type of continuous and discrete random variables, we do not have a general type of independent test. In this study, we develop a independence test of a continuous random variable and a discrete random variable without assuming a specific distribution using kernel density estimation. We provide some statistical criteria to test independence under some special settings and apply the proposed independence test to Pima Indian diabetes data. Through simulations, we calculate false positive rates and true positive rates to compare the proposed test and Kolmogorov-Smirnov test.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.283-285
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• 2005

To account for the importance of variable in multi-sensor data fusion, random forests are applied to supervised land-cover classification. The random forests approach is a non-parametric ensemble classifier based on CART-like trees. Its distinguished feature is that the importance of variable can be estimated by randomly permuting the variable of interest in all the out-of-bag samples for each classifier. Supervised classification with a multi-sensor remote sensing data set including optical and polarimetric SAR data was carried out to illustrate the applicability of random forests. From the experimental result, the random forests approach could extract important variables or bands for land-cover discrimination and showed good performance, as compared with other non-parametric data fusion algorithms.