• Title/Summary/Keyword: parameters estimation

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Confidence Intervals and Joint Confidence Regions for the Two-Parameter Exponential Distribution based on Records

  • Asgharzadeh, A.;Abdi, M.
    • Communications for Statistical Applications and Methods
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    • v.18 no.1
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    • pp.103-110
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    • 2011
  • Exponential distribution is widely adopted as a lifetime model. Many authors have considered the interval estimation of the parameters of two-parameter exponential distribution based on complete and censored samples. In this paper, we consider the interval estimation of the location and scale parameters and the joint confidence region of the parameters of two-parameter exponential distribution based on upper records. A simulation study is done for the performance of all proposed confidence intervals and regions. We also propose the predictive intervals of the future records. Finally, a numerical example is given to illustrate the proposed methods.

PPGA-Based Optimal Tuning of a Digital PID Controller (PPGA에 기초한 디지털 PID 제어기의 최적 동조)

  • Shin, Myung-Ho;Kim, Min-Jeong;Lee, Yun-Hyung;So, Myung-Ok;Jin, Gang-Gyoo
    • Proceedings of the Korean Society of Marine Engineers Conference
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    • 2005.06a
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    • pp.314-320
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    • 2005
  • In this paper, a methodology for estimating the parameters of a discrete-time system and designing a digital PID controller based on the estimated model and a genetic algorithm is presented. To deal with optimization problems occurring regarding parameter estimation and controller design, a pseudo parallel genetic algorithm (PPGA) is used. The parameters of a discrete-time system are estimated using both the model technique and a PPGA. The digital PID controller is described by the pulse transfer function and its parameters are tuned based on both the model reference technique and another PPGA. A set of experimental works on two processes are carried out to illustrate the performance of the proposed method.

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Non-convex penalized estimation for the AR process

  • Na, Okyoung;Kwon, Sunghoon
    • Communications for Statistical Applications and Methods
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    • v.25 no.5
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    • pp.453-470
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    • 2018
  • We study how to distinguish the parameters of the sparse autoregressive (AR) process from zero using a non-convex penalized estimation. A class of non-convex penalties are considered that include the smoothly clipped absolute deviation and minimax concave penalties as special examples. We prove that the penalized estimators achieve some standard theoretical properties such as weak and strong oracle properties which have been proved in sparse linear regression framework. The results hold when the maximal order of the AR process increases to infinity and the minimal size of true non-zero parameters decreases toward zero as the sample size increases. Further, we construct a practical method to select tuning parameters using generalized information criterion, of which the minimizer asymptotically recovers the best theoretical non-penalized estimator of the sparse AR process. Simulation studies are given to confirm the theoretical results.

Watershed Runoff Analysis by SSARR Model (SSARR모형에 의한 유역유출 해석)

  • 안상진;이용수
    • Water for future
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    • v.22 no.1
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    • pp.109-116
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    • 1989
  • An attempt is made to describe the theory an computer algorithm of the SSARR model, and to try it's application to the small satershed, by using the estimation of the model parameters with the data of Bochong stream basin. The selected period of the hydrological data is from 1982 to 1988 for the modeling. The selected basin is the Bochong stream basin which is one of the tributaries of Geum river. The estimation of model parameters and sensitivity test are carried out for the analysis of the characteristics of model parameters.

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A Study on Evacuation of Patients in Hospitals : Part II (병원 피난에 관한 연구 : Part II)

  • Kim Eung-Sik;Lee Jeong-Su;Park Seong-Min;You Hee-Kwon
    • Fire Science and Engineering
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    • v.19 no.3 s.59
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    • pp.28-36
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    • 2005
  • The goal of this study is establishment of egress parameters and algorithm for estimation of total egress time in hospitals. Therefore, egress parameters should be measured and analyzed via the experiment at many hospitals. In this study, 4 general hospitals were experimented and egress parameters were measured, the comparison between experimental results and estimated total egress time were carried out. The algorithm for estimation of total egress time can be applied to other hospitals.

Bayesian estimation of ordered parameters (순서화 모수에 대한 베이지안 추정)

  • 정광모;정윤식
    • The Korean Journal of Applied Statistics
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    • v.9 no.1
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    • pp.153-164
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    • 1996
  • We discussed estimation of parameters using Gibbs sampler under order restriction on the parameters. Two well-knwon probability models, ordered exponential family and binomial distribution, are considered. We derived full conditional distributions(FCD) and also used one-for-one sampling algorithm to sample from the FCD's under order restrictions. Finally through two real data sets we compared three kinds of estimators; isotonic regression estimator, isotonic Bayesian estimator and the estimator using Gibbs sampler.

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A Study on Estimation of Cooling Load Using Forecasted Weather Data (기상 예보치를 이용한 냉방부하 예측 기법에 관한 연구)

  • Han, Kyu-Hyun;Yoo, Seong-Yeon;Lee, Je-Myo
    • Proceedings of the SAREK Conference
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    • 2008.06a
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    • pp.937-942
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    • 2008
  • In this paper, new methodology is proposed to estimate the cooling load using design parameters of building and predicted weather data. Only two parameters such as maximum and minimum temperature are necessary to obtain hourly distribution of cooling load for the next day. The maximum and minimum temperature that are used for input parameters can be obtained from forecasted weather data. Benchmarking building(research building) is selected to validate the performance of the proposed method, and the estimated cooling loads in hourly bases are calculated and compared with the measured data for benchmarking building. The estimated results show fairly good agreement with the measured data for benchmarking building.

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Studies on the Computerization of Reliability Paper (Ⅵ) (신뢰성 확률지의 전산화에 관한 연구 (Ⅵ))

  • 정수일
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.22 no.50
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    • pp.373-380
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    • 1999
  • This paper summerizes the former 5 papers that studied computer programming for the estimation of the Weibull, Extreme value, Hazard, Normal and Log-normal parameters which have a close relation with the reliability of the various kinds of industrial products. Probability paper is very commonly used in estimating the parameters, however, it is very hard to neglect the errors in plotting the data, and especially in drawing the regression line. The main purpose of this paper is to reduce these errors and to help the engineers to use the parameters in improving the reliability of their prod- ucts. The following parts are included in the computer programming with the em- phases on significant digits and rounding of numerical values : $\bullet$ data input part for various cases $\bullet$ parameter estimation part $\bullet$ printing part for input data $\bullet$ printing part for the results $\bullet$ printing part for the graphic(probability paper). And the running results(monitor displays) of the program for a fictitious example of Weibull distribution is given for the interested ones.

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The Design of Hybrid Fuzzy Controller Based on Parameter Estimation Mode Using Genetic Algorithms (유전자 알고리즘을 이용한 파라미터 추정모드기반 하이브리드 퍼지 제어기의 설계)

  • 이대근;오성권;장성환
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.05a
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    • pp.228-231
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    • 2000
  • A hybrid fuzzy controller by means of the genetic algorithms is presented. The control input for the system in the HFC is a convex combination of the FLC's output in transient state and PlD's output in steady state by a fuzzy variable. The HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance than any other controller. A auto-tuning algorithms is presented to automatically improve the performance of hybrid fuzzy controller using genetic algorithms. The algorithms estimates automatical Iy the optimal values of scaling factors, PID parameters and membership function parameters of fuzzy control rules. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA three kinds of estimation modes are effectively utilized. The HFCs are applied to the second process with time-delay. Computer simulations are conducted at step input and the performances of systems are evaluated and also discussed in ITAE(Integral of the Time multiplied by the Absolute value of Error ) and other ways.

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Application of Bayesian Computational Techniques in Estimation of Posterior Distributional Properties of Lognormal Distribution

  • Begum, Mun-Ni;Ali, M. Masoom
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.1
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    • pp.227-237
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    • 2004
  • In this paper we presented a Bayesian inference approach for estimating the location and scale parameters of the lognormal distribution using iterative Gibbs sampling algorithm. We also presented estimation of location parameter by two non iterative methods, importance sampling and weighted bootstrap assuming scale parameter as known. The estimates by non iterative techniques do not depend on the specification of hyper parameters which is optimal from the Bayesian point of view. The estimates obtained by more sophisticated Gibbs sampler vary slightly with the choices of hyper parameters. The objective of this paper is to illustrate these tools in a simpler setup which may be essential in more complicated situations.

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