• Title/Summary/Keyword: interval variables

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An iterative hybrid random-interval structural reliability analysis

  • Fang, Yongfeng;Xiong, Jianbin;Tee, Kong Fah
    • Earthquakes and Structures
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    • v.7 no.6
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    • pp.1061-1070
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    • 2014
  • An iterative hybrid structural dynamic reliability prediction model has been developed under multiple-time interval loads with and without consideration of stochastic structural strength degradation. Firstly, multiple-time interval loads have been substituted by the equivalent interval load. The equivalent interval load and structural strength are assumed as random variables. For structural reliability problem with random and interval variables, the interval variables can be converted to uniformly distributed random variables. Secondly, structural reliability with interval and stochastic variables is computed iteratively using the first order second moment method according to the stress-strength interference theory. Finally, the proposed method is verified by three examples which show that the method is practicable, rational and gives accurate prediction.

Interval prediction on the sum of binary random variables indexed by a graph

  • Park, Seongoh;Hahn, Kyu S.;Lim, Johan;Son, Won
    • Communications for Statistical Applications and Methods
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    • v.26 no.3
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    • pp.261-272
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    • 2019
  • In this paper, we propose a procedure to build a prediction interval of the sum of dependent binary random variables over a graph to account for the dependence among binary variables. Our main interest is to find a prediction interval of the weighted sum of dependent binary random variables indexed by a graph. This problem is motivated by the prediction problem of various elections including Korean National Assembly and US presidential election. Traditional and popular approaches to construct the prediction interval of the seats won by major parties are normal approximation by the CLT and Monte Carlo method by generating many independent Bernoulli random variables assuming that those binary random variables are independent and the success probabilities are known constants. However, in practice, the survey results (also the exit polls) on the election are random and hardly independent to each other. They are more often spatially correlated random variables. To take this into account, we suggest a spatial auto-regressive (AR) model for the surveyed success probabilities, and propose a residual based bootstrap procedure to construct the prediction interval of the sum of the binary outcomes. Finally, we apply the procedure to building the prediction intervals of the number of legislative seats won by each party from the exit poll data in the $19^{th}$ and $20^{th}$ Korea National Assembly elections.

The hybrid uncertain neural network method for mechanical reliability analysis

  • Peng, Wensheng;Zhang, Jianguo;You, Lingfei
    • International Journal of Aeronautical and Space Sciences
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    • v.16 no.4
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    • pp.510-519
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    • 2015
  • Concerning the issue of high-dimensions, hybrid uncertainties of randomness and intervals including implicit and highly nonlinear limit state function, reliability analysis based on the hybrid uncertainty reliability mode combining with back propagation neural network (HU-BP neural network) is proposed in this paper. Random variables and interval variables are as input layer of the neural network, after the training and approximation of the neural network, the response variables are obtained through the output layer. Reliability index is calculated by solving the optimization model of the most probable point (MPP) searching in the limit state band. Two numerical cases are used to demonstrate the method proposed in this paper, and finally the method is employed to solving an engineering problem of the aerospace friction plate. For this high nonlinear, small failure probability problem with interval variables, this method could achieve a good analysis result.

AXIOMATIC CHARACTERIZATIONS OF SIGNED INTERVAL-VALUED CHOQUET INTEGRALS

  • Jang, Lee-Chae
    • Journal of applied mathematics & informatics
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    • v.24 no.1_2
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    • pp.489-503
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    • 2007
  • In this paper, we define signed interval-valued Choquet integrals which have numerous applications in mathematical economics, informatiom theory, expected utility theory, and risk analysis on interval-valued random variables, for examples: interval-valued random payments and interval-valued random profiles, etc. And we discuss axiomatic characterizations of them. Furthermore, we fine some condition that comonotonic additivity of symmetric Choquet integrals on interval-valued random payments is satisfied and give two examples related the main theorem.

Economic Design of Variable Sampling Interval X Control Chart Using a Surrogate Variable (대용변수를 이용한 가변형 부분군 채취 간격 X 관리도의 경제적 설계)

  • Lee, Tae-Hoon;Lee, Jooho;Lee, Minkoo
    • Journal of Korean Institute of Industrial Engineers
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    • v.39 no.5
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    • pp.422-428
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    • 2013
  • In many cases, an $\bar{X}$ control chart which is based on the performance variable is used in industrial fields. However, if the performance variable is too costly or impossible to measure and a less expensive surrogate variable is available, the process may be more efficiently controlled using surrogate variables. In this paper, we propose a model for the economic design of a VSI (Variable Sampling Interval) $\bar{X}$ control chart using a surrogate variable that is linearly correlated with the performance variable. The total average profit model is constructed, which involves the profit per cycle time, the cost of sampling and testing, the cost of detecting and eliminating an assignable cause, and the cost associated with production during out-of-control state. The VSI $\bar{X}$ control charts using surrogate variables are expected to be superior to the Shewhart FSI (Fixed Sampling Interval) $\bar{X}$ control charts using surrogate variables with respect to the expected profit per unit cycle time from economic viewpoint.

Investigations into Coarsening Continuous Variables

  • Jeong, Dong-Myeong;Kim, Jay-J.
    • The Korean Journal of Applied Statistics
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    • v.23 no.2
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    • pp.325-333
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    • 2010
  • Protection against disclosure of survey respondents' identifiable and/or sensitive information is a prerequisite for statistical agencies that release microdata files from their sample surveys. Coarsening is one of popular methods for protecting the confidentiality of the data. Grouped data can be released in the form of microdata or tabular data. Instead of releasing the data in a tabular form only, having microdata available to the public with interval codes with their representative values greatly enhances the utility of the data. It allows the researchers to compute covariance between the variables and build statistical models or to run a variety of statistical tests on the data. It may be conjectured that the variance of the interval data is lower that of the ungrouped data in the sense that the coarsened data do not have the within interval variance. This conjecture will be investigated using the uniform and triangular distributions. Traditionally, midpoint is used to represent all the values in an interval. This approach implicitly assumes that the data is uniformly distributed within each interval. However, this assumption may not hold, especially in the last interval of the economic data. In this paper, we will use three distributional assumptions - uniform, Pareto and lognormal distribution - in the last interval and use either midpoint or median for other intervals for wage and food costs of the Statistics Korea's 2006 Household Income and Expenditure Survey(HIES) data and compare these approaches in terms of the first two moments.

Effects of Mulligan's Mobilization with Movement on Talofibular Interval in Subjects with Chronic Ankle Instability

  • Koh, Eun-Kyung;Jung, Do-Young
    • The Journal of Korean Physical Therapy
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    • v.28 no.5
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    • pp.303-307
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    • 2016
  • Purpose: This study was conducted to determine the effects of Mulligan's mobilization with movement (MWM) on changes in the talofibular interval in the sagittal plane in subjects with chronic ankle instability (CAI). Methods: Sixteen subjects with chronic ankle instability participated in this study. The talofibular intervals were measured from US images, and the weight-bearing lunge test was used to assess dorsiflexion of the ankle joint. Each dependent variable were measured on the both affected side and sound side in three trials in pre- and post-MWM. Dependent variables were examined with a two-way mixed-design analysis of variance (ANOVA). The two factors were side (sound side versus affected side) and intervention (pre- versus post-intervention). For post hoc analysis, paired t-tests were performed to compare the dependent variables. A p<0.05 was considered to indicate significance. Results: Dorsiflexion and talofibular interval differed significantly pre- and post-intervention (p<0.05). Post-hoc analysis revealed that the talofibular interval post-MWM was significantly less than that pre-MWM on the both the affected and sound side (p<0.05). The ankle dorsiflexion in the post-MWM group was significantly greater than that in the pre-MWM group on the affected side and the sound side (p<0.05). Conclusion: The Mulligan's MWM decreased the talofibular interval in subjects with CAI. These findings suggest that the MWM technique can change the position of the talus relative to the fibular in the weight bearing position.

On Assessing Inter-observer Agreement Independent of Variables' Measuring Units

  • Um, Yong-Hwan
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.2
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    • pp.529-536
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    • 2006
  • Investigators use either Euclidean distance or volume of a simplex defined composed of data points as agreement index to measure chance-corrected agreement among observers for multivariate interval data. The agreement coefficient proposed by Um(2004) is based on a volume of a simplex and does not depend on the variables' measuring units. We consider a comparison of Um(2004)'s agreement coefficient with others based on two unit-free distance measures, Pearson distance and Mahalanobis distance. Comparison among them is made using hypothetical data set.

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Optimal Number of Failures before Group Replacement under Minimal Repair

  • Young Kwan, Yoo
    • Journal of the Korea Safety Management & Science
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    • v.6 no.1
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    • pp.61-70
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    • 2004
  • In this paper, a group replacement policy based on a failure count is analysed. For a group of identical repairable units, a maintenance policy is performed with two phase considerations: a repair interval phase and a waiting interval phase. Each unit undergoes minimal repair at failure during the repair interval. Beyond the interval, no repair is made until a number of failures. The expected cost rate expressions under the policy is derived. A method to obtain the optimal values of decision variables are explored. Numerical examples are given to demonstrate the results.

Sequential Estimation of variable width confidence interval for the mean

  • Kim, Sung Lai
    • Journal of the Chungcheong Mathematical Society
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    • v.14 no.2
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    • pp.47-54
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    • 2001
  • Let {Xn, n = 1,2,${\cdots}$} be i.i.d. random variables with the only unknown parameters mean ${\mu}$ and variance a ${\sigma}^2$. We consider a sequential confidence interval C1 for the mean with coverage probability 1-${\alpha}$ and expected length of confidence interval $E_{\theta}$(Length of CI)/${\mid}{\mu}{\mid}{\leq}k$ (k : constant) and give some asymptotic properties of the stopping time in various limiting situations.

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