• Title/Summary/Keyword: interval probability

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Evaluating Interval Estimates for Comparing Two Proportions with Rare Events

  • Park, Jin-Kyung;Kim, Yong-Dai;Lee, Hak-Bae
    • The Korean Journal of Applied Statistics
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    • v.25 no.3
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    • pp.435-446
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    • 2012
  • Epidemiologic studies frequently try to estimate the impact of a specific risk factor. The risk difference and the risk ratio are generally useful measurements for this purpose. When using such measurements for rare events, the standard approaches based on the normal approximation may fail, in particular when no events are observed. In this paper, we discuss and evaluate several existing methods to construct confidence intervals around risk differences and risk ratios using Monte-Carlo simulations when the disease of interest is rare. The results in this paper provide guidance how to construct interval estimates of the risk differences and the risk ratios when no events are detected.

The Influence of Extreme Value in Binomial Confidence Interval (이항 신뢰구간에서 극단값의 영향)

  • Ryu, Jea-Bok
    • Communications for Statistical Applications and Methods
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    • v.18 no.5
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    • pp.615-623
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    • 2011
  • Several methods are used in interval estimation for binomial proportion; however the coverage probabilities of most confidence intervals depart from the confidence level when the binomial population proportion closes to 0 or 1 due to the extreme value. Vollset (1993), Agresti and Coull (1998), Newcombe (1998), and Brown et al. (2001) suggested methods to adjust the extreme value. This paper discusses the influence of extreme value in a binomial confidence interval through the numerical comparison of 6 confidence intervals.

Optimizing Checkpoint Intervals for Real-Time Multi-Tasks with Arbitrary Periods (임의 주기를 가지는 실시간 멀티 태스크를 위한 체크포인트 구간 최적화)

  • Kwak, Seong-Woo;Yang, Jung-Min
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.1
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    • pp.193-200
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    • 2011
  • This paper presents an optimal checkpoint strategy for fault-tolerance in real-time systems. In our environment, multiple real-time tasks with arbitrary periods are scheduled in the system by Rate Monotonic (RM) algorithm, and checkpoints are inserted at a constant interval in each task while the width of interval is different with respect to the task. We propose a method to determine the optimal checkpoint interval for each task so that the probability of completing all the tasks is maximized. Whenever a fault occurs to a checkpoint interval of a task, the execution time of the task would be prolonged by rollback and re-execution of checkpoints. Our scheme includes the schedulability test to examine whether a task can be completed with an extended execution time. A numerical experiment is conducted to demonstrate the applicability of the proposed scheme.

Nonpararmetric estimation for interval censored competing risk data

  • Kim, Yang-Jin;Kwon, Do young
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.4
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    • pp.947-955
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    • 2017
  • A competing risk analysis has been applied when subjects experience more than one type of end points. Geskus (2011) showed three types of estimators of CIF are equivalent under left truncated and right censored data. We extend his approach to an interval censored competing risk data by using a modified risk set and evaluate their performance under several sample sizes. These estimators show very similar results. We also suggest a test statistic combining Sun's test for interval censored data and Gray's test for right censored data. The test sizes and powers are compared under several cases. As a real data application, the suggested method is applied a data where the feasibility of the vaccine to HIV was assessed in the injecting drug uses.

Reinforcement Learning-based Duty Cycle Interval Control in Wireless Sensor Networks

  • Akter, Shathee;Yoon, Seokhoon
    • International journal of advanced smart convergence
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    • v.7 no.4
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    • pp.19-26
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    • 2018
  • One of the distinct features of Wireless Sensor Networks (WSNs) is duty cycling mechanism, which is used to conserve energy and extend the network lifetime. Large duty cycle interval introduces lower energy consumption, meanwhile longer end-to-end (E2E) delay. In this paper, we introduce an energy consumption minimization problem for duty-cycled WSNs. We have applied Q-learning algorithm to obtain the maximum duty cycle interval which supports various delay requirements and given Delay Success ratio (DSR) i.e. the required probability of packets arriving at the sink before given delay bound. Our approach only requires sink to compute Q-leaning which makes it practical to implement. Nodes in the different group have the different duty cycle interval in our proposed method and nodes don't need to know the information of the neighboring node. Performance metrics show that our proposed scheme outperforms existing algorithms in terms of energy efficiency while assuring the required delay bound and DSR.

System RBDO of truss structures considering interval distribution parameters

  • Zaeimi, Mohammad;Ghoddosian, Ali
    • Structural Engineering and Mechanics
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    • v.70 no.1
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    • pp.81-96
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    • 2019
  • In this paper, a hybrid uncertain model is applied to system reliability based design optimization (RBDO) of trusses. All random variables are described by random distributions but some key distribution parameters of them which lack information are defined by variation intervals. For system RBDO of trusses, the first order reliability method, as well as monotonicity analysis and the branch and bound method, are utilized to determine the system failure probability; and Improved (${\mu}+{\lambda}$) constrained differential evolution (ICDE) is employed for the optimization process. System reliability assessment of several numerical examples and system RBDO of different truss structures are proposed to verify our results. Moreover, the effect of different classes of interval distribution parameters on the optimum weight of the structure and the reliability index are also investigated. The results indicate that the weight of the structure is increased by increasing the uncertainty level. Moreover, it is shown that for a certain random variable, the optimum weight is more increased by the translation interval parameters than the rotation ones.

RADO'S AND POPONOV'S INEQUALITIES OF PROBABILITY MEASURES FOR POSITIVE REAL NUMBERS

  • Lee, Hosoo;Kim, Sejong
    • Journal of the Chungcheong Mathematical Society
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    • v.27 no.2
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    • pp.165-172
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    • 2014
  • In this paper, we derive some valuable inequalities of Rado's and Poponov's types on the open interval of positive real numbers, and then show weighted generalizations of Rado's and Poponov's inequalities on the set of positive real numbers equipped with compactly supported probability measure.

A Comparison of Some Approximate Confidence Intervals for he Poisson Parameter

  • Kim, Daehak;Jeong, Hyeong-Chul
    • Communications for Statistical Applications and Methods
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    • v.7 no.3
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    • pp.899-911
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    • 2000
  • In this paper, we reviewed thirteen methods for finding confidence intervals for he mean of poisson distribution. Bootstrap confidence intervals are also introduced. Two bootstrap confidence intervals are compared with the other existing eleven confidence intervals by using Monte Carlo simulation with respect to the average coverage probability of Woodroofe and Jhun (1989).

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Sequential Estimation with $\beta$-Protection of the Difference of Two Normal Means When an Imprecision Function Is Variable

  • Kim, Sung-Lai;Kim, Sung-Kyun
    • Journal of the Korean Statistical Society
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    • v.31 no.3
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    • pp.379-389
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    • 2002
  • For two normal distribution with unknown means and unknown variances, a sequential procedure for estimating the difference of two normal means which satisfies both the coverage probability condition and the $\beta$-protection is proposed under some smoothness of variable imprecision function, and the asymptotic normality of the proposed stopping time after some centering and scaling is given.

A comparative analysis of the 2009-revised curriculum and 2015-revised curriculum on the definition and introduction of continuous probability distribution (연속확률분포의 정의와 도입 방법에 대한 2009개정 교육과정과 2015개정 교육과정의 비교 분석 연구)

  • Heo, Nam Gu
    • The Mathematical Education
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    • v.58 no.4
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    • pp.531-543
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    • 2019
  • Continuous probability distribution was one of the mathematics concept that students had difficulty. This study analyzed the definition and introduction of the continuous probability distribution under the 2009-revised curriculum and 2015-revised curriculum. In this study, the following subjects were studied. Firstly, definitions of continuous probability variable in 'Probability and Statistics' textbook developed under the 2009-revised curriculum and 2015-revised curriculum were analyzed. Secondly, introductions of continuous probability distribution in 'Probability and Statistics' textbook developed under the 2009-revised curriculum and 2015-revised curriculum were analyzed. The results of this study were as follows. First, 8 textbooks under the 2009-revised curriculum defined the continuous probability variable as probability variable with all the real values within a range or an interval. And 1 textbook under the 2009-revised curriculum defined the continuous probability variable as probability variable when the set of its value is uncountable. But all textbooks under the 2015-revised curriculum defined the continuous probability variable as probability variable with all the real values within a range. Second, 4 textbooks under the 2009-revised curriculum and 4 textbooks under 2015-revised curriculum introduced a continuous random distribution using an uniformly distribution. And 5 textbooks under the 2009-revised curriculum and 5 textbooks under the 2015-revised curriculum introduced a continuous random distribution using a relative frequency density.