• 제목/요약/키워드: Random variable

검색결과 906건 처리시간 0.03초

Improved Exponential Estimator for Estimating the Population Mean in the Presence of Non-Response

  • Kumar, Sunil
    • Communications for Statistical Applications and Methods
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    • 제20권5호
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    • pp.357-366
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    • 2013
  • This paper defines an improvement for estimating the population mean of a study variable using auxiliary information and known values of certain population parameter(s), when there is a non-response in a study as well as on auxiliary variables. Under a simple random sampling without a replacement (SRSWOR) scheme, the mean square error (MSE) of all proposed estimators are obtained and compared with each other. Numerical illustration is also given.

ON CONVERGENCE OF SERIES OF INDEPENDENTS RANDOM VARIABLES

  • Sung, Soo-Hak;Volodin, Andrei-I.
    • 대한수학회보
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    • 제38권4호
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    • pp.763-772
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    • 2001
  • The rate of convergence for an almost surely convergent series $S_n={\Sigma^n}_{i-1}X_i$ of independent random variables is studied in this paper. More specifically, when S$_{n}$ converges almost surely to a random variable S, the tail series $T_n{\equiv}$ S - S_{n-1} = {\Sigma^\infty}_{i-n} X_i$ is a well-defined sequence of random variables with T$_{n}$ $\rightarrow$ 0 almost surely. Conditions are provided so that for a given positive sequence {$b_n, n {\geq$ 1}, the limit law sup$_{\kappa}\geqn | T_{\kappa}|/b_n \rightarrow$ 0 holds. This result generalizes a result of Nam and Rosalsky [4].

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ON THE STRONG LAW OF LARGE NUMBERS FOR WEIGHTED SUMS OF ARRAYS OF ROWWISE NEGATIVELY DEPENDENT RANDOM VARIABLES

  • Baek, Jong-Il;Seo, Hye-Young;Lee, Gil-Hwan;Choi, Jeong-Yeol
    • 대한수학회지
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    • 제46권4호
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    • pp.827-840
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    • 2009
  • Let {$X_{ni}$ | $1{\leq}i{\leq}n,\;n{\geq}1$} be an array of rowwise negatively dependent (ND) random variables. We in this paper discuss the conditions of ${\sum}^n_{t=1}a_{ni}X_{ni}{\rightarrow}0$ completely as $n{\rightarrow}{\infty}$ under not necessarily identically distributed setting and the strong law of large numbers for weighted sums of arrays of rowwise negatively dependent random variables is also considered.

퍼지-랜덤 변수를 이용한 DES 모델링을 통한 실시간 전력 시스템의 성능 및 신뢰도 평가 (Evaluation of the Performance and Reliability of a Real-time Power System Described by a DES Model using Fuzzy-Random Variables)

  • 민병조;이석주;김학배
    • 대한전기학회논문지:시스템및제어부문D
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    • 제49권7호
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    • pp.363-369
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    • 2000
  • To flexibly evaluate performance and reliability of an electric power system in the aspect of the real-time system which is intrinsically characterized by stringent timing constraints fails catastrophically if its control input is not updated by its digital controller computer within a certain time limit called the hard deadline, we propose fuzzy-random variables and build a discrete event model embedded with fuzzy-random variables. Also, we adapt fuzzy-variables to a path-space approach, which derives the upper and lower bounds of reliability by using a semi-Markov model that explicitly contains the deadline information. Consequently, we propose certain formulas of state automata properly transformed by fuzzy-random variables, and present numerical examples applying the formulas as well.

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유도전동기의 소음저감을 위한 DSP기반 PWM인버터의 랜덤 캐리어 주파수 변조기법의 구현 (Implementation of Random Carrier-Frequency Modulation Scheme for a DSP based PWM Inverter for Acoustic Noise Reduction of Induction Motors)

  • 정영국;나석환;임영철;정성기
    • 대한전기학회논문지:전기기기및에너지변환시스템부문B
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    • 제52권12호
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    • pp.608-615
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    • 2003
  • This paper describes an implementation of a DSP (Digital Signal Processor) controlled random carrier frequency modulation for the PWM inverter for acoustic noise reduction of induction motors. Real-time generation of the random variable and RPWM(Random PWM) along with the speed control was achieved by DSP TMS320C31. The experimental results show that the voltage and current harmonics are spread to a wide band area and the power spectrum of the acoustic switching noise was spread to create a more appealing, less annoying sound. Also, the speed response of the implemented method and the conventional method is nearly similar to each other from the viewpoint of the v/f constant control.

An INS Filter Design Considering Mixed Random Errors of Gyroscopes

  • Seong, Sang-Man;Kang, Ki-Ho
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.262-264
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    • 2005
  • We propose a filter design method to suppress the effect of gyroscope mixed random errors at INS system level. It is based on the result that mixed random errors can be represented by a single equivalent ARMA model. At first step, the time difference of equivalent ARMA process is performed, which consider the characteristic of indirect feedback Kalman filter used in INS filter. Next, a state space conversion of time differenced ARMA model is achieved. If the order of AR is greater than that of MA, the controllable or observable canonical form is used. Otherwise, we introduce the state equation of which the state variable is composed of the ARMA model output and several step ahead predicts of that. At final step, a complete form state equation is presented. The simulation results shows that the proposed method gives less transient error and better convergence compared to the conventional filter which assume the mixed random errors as white noise.

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방파제를 통과하는 규칙파와 다방향 불규칙파랑의 거동 (Behavior of Regular Waves and Multi-Directional Random Waves Passing a Breakwater)

  • 박상일;박진호;조용식
    • 한국방재학회:학술대회논문집
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    • 한국방재학회 2008년도 정기총회 및 학술발표대회
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    • pp.439-442
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    • 2008
  • Diffraction of multi-directional random waves passing semi-infinite breakwater is investigated by using analytic solution derived by Penny and Prices(1952). An irregylarity of period and incident angle of waves and regular periods for regular waves are considered in addition by expanding from the past study which used only monochromatic wave in general. The Bretschneider-Mitsuyasu frequency spectrum and Mitsuyasu directional spectrum are used for incident waves. And diffraction of multi-directional random waves is reappeared by decomposing numerical results of several monochromatic waves which have variable period and incident angle. Analytic solution on the diffraction of regular waves and multi-directional random waves calculated in this study.

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Design of the Variable Sampling Rates X-chart with Average Time to Signal Adjusted by the Sampling Cost

  • Park, Chang-Soon;Song, Moon-Sup
    • Journal of the Korean Statistical Society
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    • 제26권2호
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    • pp.181-198
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    • 1997
  • The variable sampling rates scheme is proposed by taking random sample size and sampling interval during the process. The performance of the scheme is measured in terms of the average time to signal adjusted by teh sampling cost when the process is out of control. This measurement evaluates the effectiveness of the scheme in terms of the cost incurred due to nonconformation as well as sampling. The variable sampling rates scheme is shown to be effective especially for small and moderate shifts of the mean when compared to the standard scheme.

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선형성장모형에 대한 ROC 곡선과 AUC (ROC curve and AUC for linear growth models)

  • 홍종선;양대순
    • Journal of the Korean Data and Information Science Society
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    • 제26권6호
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    • pp.1367-1375
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    • 2015
  • 경시적자료의 분석으로 선형성장모형을 고려한다. 시간효과를 고려하는 모형과 임의효과를 추가하는 모형 그리고 가변수가 추가된 모형을 설정한다. 본 연구는 정규분포로 가정한 다양한 자료를 생성하고, 다양한 선형성장모형에 대하여 binormal ROC 곡선과 AUC 통계량을 여러 시점에서 구하여 비교 분석하였다. 공분산의 크기가 증가할수록 그리고 시간이 경과할수록 ROC 곡선은 다른 형태로 나타나며 AUC 값은 서서히 증가한다. 반대로 공분산이 작아질수록 시간이 경과함에 따라 AUC의 증가폭이 커진다. 임의효과모형에서 공분산이 양인 경우에 시간이 경과할수록 임의효과모형의 분산이 증가하며 AUC의 증가량은 시간효과모형의 AUC의 증가량보다 작다. 그리고 시간효과모형의 AUC의 증가량보다 임의효과모형의 증가량이 더 크다는 것을 탐색하였다.

생존분석에서의 기계학습 (Machine learning in survival analysis)

  • 백재욱
    • 산업진흥연구
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    • 제7권1호
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    • pp.1-8
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    • 2022
  • 본 논문은 중도중단 데이터가 포함된 생존데이터의 경우 적용할 수 있는 기계학습 방법에 대해 살펴보았다. 우선 탐색적인 자료분석으로 각 특성에 대한 분포, 여러 특성들 간의 관계 및 중요도 순위를 파악할 수 있었다. 다음으로 독립변수에 해당하는 여러 특성들과 종속변수에 해당하는 특성(사망여부) 간의 관계를 분류문제로 보고 logistic regression, K nearest neighbor 등의 기계학습 방법들을 적용해본 결과 적은 수의 데이터이지만 통상적인 기계학습 결과에서와 같이 logistic regression보다는 random forest가 성능이 더 좋게 나왔다. 하지만 근래에 성능이 좋다고 하는 artificial neural network나 gradient boost와 같은 기계학습 방법은 성능이 월등히 좋게 나오지 않았는데, 그 이유는 주어진 데이터가 빅데이터가 아니기 때문인 것으로 판명된다. 마지막으로 Kaplan-Meier나 Cox의 비례위험모델과 같은 통상적인 생존분석 방법을 적용하여 어떤 독립변수가 종속변수 (ti, δi)에 결정적인 영향을 미치는지 살펴볼 수 있었으며, 기계학습 방법에 속하는 random forest를 중도중단 데이터가 포함된 생존데이터에도 적용하여 성능을 평가할 수 있었다.