• Title/Summary/Keyword: Distribution of sample mean

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Empirical Evidence on Scope Effects in Contingent Valuation of Water Quality Improvement in Man Kyoung River (만경강 수질개선 편익측정을 위한 조건부가치평가에 있어서 범위효과 분석)

  • Eom, Young Sook
    • Environmental and Resource Economics Review
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    • v.10 no.3
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    • pp.387-412
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    • 2001
  • This paper is to empirically test scope effects proposed to judge the internal consistency of contingent valuation method. The application was illustrated for the case of estimating people's WTP for improving water quality at Man Kyoung River in the Chon Buk area. The CV survey was carefully designed and implemented by carrying out recommendations from the NOAA Blue Ribbon panel. Using a split sample, we conducted the Cochran-Mantel-Haenszel test with the frequency distribution of no responses, calculated the Turnbull low bound mean for WTP, and measured the mean WTP from estimated variation functions. The test results consistently exhibited that the CV estimates of WTP were adequately responsive to the size of water quality changes being offered. The mean WTP for improving water quality suitable for swimming (5,171 and 5,212 won) was significantly larger than that for agricultural use and fishing activity (3,280 and 3,136 won).

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Size Determination of Pollens Using Gravitational and Sedimentation Field-Flow Fractionation

  • Kang, Dong-Young;Son, Min-Seok;Eum, Chul-Hun;Kim, Won-Suk;Lee, Seung-Ho
    • Bulletin of the Korean Chemical Society
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    • v.28 no.4
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    • pp.613-618
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    • 2007
  • Pollens are known to be an allergen. They penetrate human respiratory system, triggering a type of seasonal allergic rhinitis called pollen allergy (hey fever). The purpose of this study is to test two field-flow fractionation (FFF) techniques, gravitational FFF (GrFFF) and sedimentation FFF (SdFFF), for their applicability to sizecharacterization of micron-sized pollens. Both GrFFF and SdFFF are elution techniques, providing sequential elution of particles based on size. They allow the size distribution as well as the mean size of the sample to be determined from the elution time. In this study, GrFFF and SdFFF were used to determine the size distribution of Paper Mulberry and Bermuda Grass pollens. For the Paper Mulberry pollen, the mean size obtained by GrFFF is 12.7 μm, and agrees rather well with the OM data with the relative error of 8.0%. For the Bermuda Grass pollen, the mean size obtained by GrFFF is 32.6 μm with the relative error of 12.3%. The mean sizes determined by SdFFF are 12.4 (relative error = 10.1%) and 27.1 μm (relative error = 5.2%) for the Paper Mulberry and the Bermuda Grass pollen, respectively. Although SdFFF tends to yield more accurate size distribution due to lower band broadening under the field strength higher than 1 G, the sizes determined by GrFFF were not significantly different from those by SdFFF.

Application of the Weibull-Poisson long-term survival model

  • Vigas, Valdemiro Piedade;Mazucheli, Josmar;Louzada, Francisco
    • Communications for Statistical Applications and Methods
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    • v.24 no.4
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    • pp.325-337
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    • 2017
  • In this paper, we proposed a new long-term lifetime distribution with four parameters inserted in a risk competitive scenario with decreasing, increasing and unimodal hazard rate functions, namely the Weibull-Poisson long-term distribution. This new distribution arises from a scenario of competitive latent risk, in which the lifetime associated to the particular risk is not observable, and where only the minimum lifetime value among all risks is noticed in a long-term context. However, it can also be used in any other situation as long as it fits the data well. The Weibull-Poisson long-term distribution is presented as a particular case for the new exponential-Poisson long-term distribution and Weibull long-term distribution. The properties of the proposed distribution were discussed, including its probability density, survival and hazard functions and explicit algebraic formulas for its order statistics. Assuming censored data, we considered the maximum likelihood approach for parameter estimation. For different parameter settings, sample sizes, and censoring percentages various simulation studies were performed to study the mean square error of the maximum likelihood estimative, and compare the performance of the model proposed with the particular cases. The selection criteria Akaike information criterion, Bayesian information criterion, and likelihood ratio test were used for the model selection. The relevance of the approach was illustrated on two real datasets of where the new model was compared with its particular cases observing its potential and competitiveness.

Customer Characteristics Modeling for Each Load Pattern using the Database (데이터베이스를 이용한 부하패턴별 수용가 특징 모델링)

  • Lee, Young-Suk;Kim, Jae-Chul;Oh, Jung-Hwan;Yun, Sang-Yun;Park, Chang-Ho
    • Proceedings of the KIEE Conference
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    • 2001.07a
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    • pp.416-418
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    • 2001
  • This Paper presents the 2-step load cycle of daily load curve for representative load pattern of power distribution transformer. We decide the representative load pattern of distribution transformer in domestic using the pattern classification algorithm. The K-mean method is used for the pattern classification algorithm. The acquisition equipment of field load data is utilized for 96-sample distribution transformers and the field data is used in the construction of the database for the creation of daily load pattern.

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Kernel Inference on the Inverse Weibull Distribution

  • Maswadah, M.
    • Communications for Statistical Applications and Methods
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    • v.13 no.3
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    • pp.503-512
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    • 2006
  • In this paper, the Inverse Weibull distribution parameters have been estimated using a new estimation technique based on the non-parametric kernel density function that introduced as an alternative and reliable technique for estimation in life testing models. This technique will require bootstrapping from a set of sample observations for constructing the density functions of pivotal quantities and thus the confidence intervals for the distribution parameters. The performances of this technique have been studied comparing to the conditional inference on the basis of the mean lengths and the covering percentage of the confidence intervals, via Monte Carlo simulations. The simulation results indicated the robustness of the proposed method that yield reasonably accurate inferences even with fewer bootstrap replications and it is easy to be used than the conditional approach. Finally, a numerical example is given to illustrate the densities and the inferential methods developed in this paper.

Reliability Estimation in an Exponentiated Logistic Distribution under Multiply Type-II Censoring

  • Han, Jun-Tae;Kang, Suk-Bok;Cho, Young-Seuk
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.4
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    • pp.1081-1091
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    • 2007
  • In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and location parameter in an exponentiated logistic distribution based on multiply Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples. We also propose and compare the estimators of the reliability function by using the proposed estimators of the parameters.

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Bayesian Inference for Multinomial Group Testing

  • Heo, Tae-Young;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.81-92
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    • 2007
  • This paper consider trinomial group testing concerned with classification of N given units into one of k disjoint categories. In this paper, we propose Bayesian inference for estimating individual category proportions using the trinomial group testing model proposed by Bar-Lev et al. (2005). We compared a relative efficience (RE) based on the mean squared error (MSE) of MLE and Bayes estimators with various prior information. The impact of different prior specifications on the estimates is also investigated using selected prior distribution. The impact of different priors on the Bayes estimates is modest when the sample size and group size we large.

A Piecewise Weibull Distribution in Reliability and its Estimation (신뢰성이론에서의 피스와이즈 와이블분포와 그 추정)

  • Jeong, Hai-Sung
    • Journal of Korean Society for Quality Management
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    • v.24 no.2
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    • pp.65-76
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    • 1996
  • In general, most industrial products exhibit bath-tub shaped curve for their failure rate functions. This distributional life model can be obtained by the Piecewise Weibull distribution. The least squares, maximum likelihood, and mixed methods of estimating the parameters of the Piecewise Weibull distribution are compared. The comparison is made by using the empirical mean squared errors of (a) the parameter estimates and (b) the estimated change-points, to summarize the results of 1000 simulated samples of three sizes - each 100, 150 and 200. The results are that the mixed method estimation comes to be the best as the sample sizes increase.

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Estimation on a two-parameter Rayleigh distribution under the progressive Type-II censoring scheme: comparative study

  • Seo, Jung-In;Seo, Byeong-Gyu;Kang, Suk-Bok
    • Communications for Statistical Applications and Methods
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    • v.26 no.2
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    • pp.91-102
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    • 2019
  • In this paper, we propose a new estimation method based on a weighted linear regression framework to obtain some estimators for unknown parameters in a two-parameter Rayleigh distribution under a progressive Type-II censoring scheme. We also provide unbiased estimators of the location parameter and scale parameter which have a nuisance parameter, and an estimator based on a pivotal quantity which does not depend on the other parameter. The proposed weighted least square estimator (WLSE) of the location parameter is not dependent on the scale parameter. In addition, the WLSE of the scale parameter is not dependent on the location parameter. The results are compared with the maximum likelihood method and pivot-based estimation method. The assessments and comparisons are done using Monte Carlo simulations and real data analysis. The simulation results show that the estimators ${\hat{\mu}}_u({\hat{\theta}}_p)$ and ${\hat{\theta}}_p({\hat{\mu}}_u)$ are superior to the other estimators in terms of the mean squared error (MSE) and bias.

Bayesian Reliability Estimation of Two-Unit Rot Standby System

  • Lee, Chang-Soo;Kim, Hee-Jae;Moon, Yeung-Gil;Lee, Jang-Choon
    • Journal of the Korean Data and Information Science Society
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    • v.9 no.1
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    • pp.89-94
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    • 1998
  • We shall propose several Bayes estimators for reliability of a two-unit hot standby system with the imperfect switch based upon a complete sample of failure times observed from an exponential distribution, and the proposed reliability Bayesian estimators are compared numerically each other in sense of mean squared error.

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