• Title/Summary/Keyword: exponential model

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The Comparative Study of Software Optimal Release Time Based on Gamma Exponential and Non-exponential Family Distribution Model (지수 및 비지수족 분포 모형에 근거한 소프트웨어 최적방출시기에 관한 비교 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.5
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    • pp.125-132
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    • 2010
  • Decision problem called an optimal release policies, after testing a software system in development phase and transfer it to the user, is studied. The applied model of release time exploited infinite non-homogeneous Poisson process. This infinite non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The failure life-cycle distribution used exponential and non-exponential family which has various intensity. Thus, software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time.

Estimation of Parameters in a Generalized Exponential Semi-Markov Reliability Models

  • El-Gohary Awad
    • International Journal of Reliability and Applications
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    • v.6 no.1
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    • pp.13-29
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    • 2005
  • This paper deals with the stochastic analysis of a three-states semi-Markov reliability model. Using both the maximum likelihood and Bayes procedures, the parameters included in this model are estimated. Next, assuming that the lifetime and repair time are generalized exponential random variables, the reliability function of this system is obtained. Then, the distribution of the first passage time of this system is discussed. Finally, some of the obtained results are compared with those available in the literature.

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ON THE ADMISSIBILITY OF HIERARCHICAL BAYES ESTIMATORS

  • Kim Byung-Hwee;Chang In-Hong
    • Journal of the Korean Statistical Society
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    • v.35 no.3
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    • pp.317-329
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    • 2006
  • In the problem of estimating the error variance in the balanced fixed- effects one-way analysis of variance (ANOVA) model, Ghosh (1994) proposed hierarchical Bayes estimators and raised a conjecture for which all of his hierarchical Bayes estimators are admissible. In this paper we prove this conjecture is true by representing one-way ANOVA model to the distributional form of a multiparameter exponential family.

Uniform Ergodicity and Exponential α-Mixing for Continuous Time Stochastic Volatility Model

  • Lee, O.
    • Communications for Statistical Applications and Methods
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    • v.18 no.2
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    • pp.229-236
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    • 2011
  • A continuous time stochastic volatility model for financial assets suggested by Barndorff-Nielsen and Shephard (2001) is considered, where the volatility process is modelled as an Ornstein-Uhlenbeck type process driven by a general L$\'{e}$vy process and the price process is then obtained by using an independent Brownian motion as the driving noise. The uniform ergodicity of the volatility process and exponential ${\alpha}$-mixing properties of the log price processes of given continuous time stochastic volatility models are obtained.

Direct Model Reference Adaptive Pole Pacement Control with Exponential Weighting Properties (지수함수적 가중특성의 기준 모델 직접 적응 극배치 제어)

  • Kim, Jong-Hwan;Kwack, Jeong-Hun
    • Proceedings of the KIEE Conference
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    • 1990.07a
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    • pp.51-54
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    • 1990
  • A parametrization for a linear system is presented to design a direct model reference adaptive pole placement controler. This parametrized model is one of the structured nonminimal models. The exponentially weighted least-squres algorithm is employed to estimate the control parameters. The direct adaptive controller has the exponential weighting properties by the proposed method of selecting the characteristic polynomials of the sensitivity function filters in connection with the reference models.

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Generalized Exponential Regression Model with Randomly Censored Data (임의중도절단자료를 갖는 일반화된 지수회귀모형)

  • 하일도
    • Journal of Korea Society of Industrial Information Systems
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    • v.4 no.2
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    • pp.39-43
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    • 1999
  • We consider generalized exponential regression model with randomly censored data and propose a modified Fisher scoring method which estimates the model parameters. For this, the likelihood equations are derived and then the estimating algorithm is developed. We illustrate the proposed method using a real data.

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A Study for Improving the Positioning Accuracy of DGPS Based on Multi-Reference Stations by Applying Exponential Modeling on Pseudorange Corrections

  • Kim, Koon-Tack;Park, Kwan-Dong;Lee, Eunsung;Heo, Moon Beom
    • Journal of Positioning, Navigation, and Timing
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    • v.2 no.1
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    • pp.9-17
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    • 2013
  • In this paper, a pseudorange correction regeneration algorithm was developed to improve the positioning accuracy of DGPS using multi-reference stations, and the optimal minimum number of reference sites was determined by trying out different numbers of reference. This research was conducted using from two to five sites, and positioning errors of less than 1 m were obtained when pseudorange corrections are collected from at least four reference stations and interpolated as the pseudorange correction at the rover. After determining the optimal minimum number of reference stations, the pseudorange correction regeneration algorithm developed was tested by comparison with the performance of other algorithms. Our approach was developed based on an exponential model. If pseudorange corrections are regenerated using an exponential model, the effect of a small difference in the baseline distance can be enlarged. Therefore, weights can be applied sensitively even when the baseline distance differs by a small amount. Also weights on the baseline distance were applied differently by assigning weights depending on the difference of the longest and shortest baselines. Through this method, the positioning accuracy improved by 19% compared to the result of previous studies.

Improvement of Analytical Probabilistic Model for Urban Storm Water Simulation using 3-parameter Mixed Exponential Probability Density Function (3변수 혼합 지수 확률밀도함수를 이용한 도시지역 강우유출수의 해석적 확률모형 개선)

  • Choi, Daegyu;Jo, Deok Jun;Han, Suhee;Kim, Sangdan
    • Journal of Korean Society on Water Environment
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    • v.24 no.3
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    • pp.345-353
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    • 2008
  • In order to design storage-based non-point source management facilities, the aspect of statistical features of the entire precipitation time series should be considered since non-point source pollutions are delivered by continuous rainfall runoffs. The 3-parameter mixed exponential probability density function instead of traditional single-parameter exponential probability density function is applied to represent the probabilistic features of long-term precipitation time series and model urban stormwater runoff. Finally, probability density functions of water quality control basin overflow are derived under two extreme intial conditions. The 31-year continuous precipitation time series recorded in Busan are analyzed to show that the 3-parameter mixed exponential probability density function gives better resolution.

Bayesian reliability estimation of bivariate Marshal-Olkin exponential stress-strength model

  • Chandra, N.;Pandey, M.
    • International Journal of Reliability and Applications
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    • v.13 no.1
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    • pp.37-47
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    • 2012
  • In this article we attempted reliability analysis of a component under the stress-strength pattern with both classical as well as Bayesian techniques. The main focus is made to develop the theory for dealing the reliability problems in various circumstances for bivariate environmental set up in context of Bayesian paradigm. A stress-strength based model describes the life of a component which has strength (Y) and is subjected to stress(X). We develop the Bayes and moment estimators of reliability of a component for each of the three possible conditions, under the assumption that the two stresses (i.e. $X_1$ and $X_2$) on a component are dependent and follow a Bivariate exponential (BVE) of Marshall-Olkin distribution, the strength of a component (Y) following exponential distribution is independent of the stresses. The simulation study is performed with Markov Chain Monte Carlo technique via Gibbs sampler to obtain the estimates of Bayes estimators of reliability, are compared with moment estimators of reliabilities on the basis of absolute biases.

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