• Title/Summary/Keyword: Probability and statistics

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Efficient Controlled Selection

  • Ryu, Jea-Bok;Lee, Seung-Joo
    • Communications for Statistical Applications and Methods
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    • v.4 no.1
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    • pp.151-159
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    • 1997
  • In sample surveys, we expect preferred samples that reduce the survey cost and increase the precision of estimators will be selected. Goodman and Kish (1950) introduced controlled selection as a method of sample selection that increases the probability of drawing preferred samples, while decreases the probability of drawing nonpreferred samples. In this paper, we obtain the controlled plans using the maximum entropy principle, and when the order of nonpreferred samples is considered, we propose the algorithm to obtain a controlled plan.

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Hanwoo(Korean Cattle) Traceability Using DNA Markers

  • Yeo, Jung-Sou;Rhee, Sung-Won;Choi, Yu-Mi;Kwon, Jae-Chul;Lee, Jea-Young
    • Communications for Statistical Applications and Methods
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    • v.13 no.3
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    • pp.733-743
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    • 2006
  • To apply and evaluate the effectiveness of genetic markers on Hanwoo traceability systems, samples of 33 Hanwoo individuals from Korean elite sire families were used, and five microsatellite markers were selected finally, which were located on chromosomes different chromosomes with the end sequencing of 100 HW-YUBAC that were recorded in the NCBI by Yeungnam University. Ten major microsatellite markers were selected from alleles amplified, their frequencies, H(Heterozygosity) and PIC(Polymorphism information content) with Hardy-Weinberg equilibrium. Next, in order to evaluate the power of the markers selected on the individual animal identification, the match probability(MP) and the relatedness coefficient(R) were computed.

Nonparametric confidence intervals for quantiles based on a modified ranked set sampling

  • Morabbi, Hakime;Razmkhah, Mostafa;Ahmadi, Jafar
    • Communications for Statistical Applications and Methods
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    • v.23 no.2
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    • pp.119-129
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    • 2016
  • A new sampling method is introduced based on the idea of a ranked set sampling scheme in which taken samples in each set are dependent on previous ones. Some theoretical results are presented and distribution-free confidence intervals are derived for the quantiles of any continuous population. It is shown numerically that the proposed sampling scheme may lead to 95% confidence intervals (especially for extreme quantiles) that cannot be found based on the ordinary ranked set sampling scheme presented by Chen (2000) and Balakrishnan and Li (2006). Optimality aspects of this scheme are investigated for both coverage probability and minimum expected length criteria. A real data set is also used to illustrate the proposed procedure. Conclusions are eventually stated.

Strong Large Deviations Theorems for the Ratio of the Independent Random Variables

  • Cho, Dae-Hyeon;Jeon, Jong-Woo
    • Journal of the Korean Statistical Society
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    • v.23 no.2
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    • pp.239-250
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    • 1994
  • In this paper, we prove a strong large deviations theorem for the ratio of independent randoem variables with error rate of $O(n^{-1})$. To obtain our results we use the inversion formula for the tail probability and apply the Chaganty and Sethuraman's (1985) approach.

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Empirical modelling approaches to modelling failures

  • Baik, Jaiwook;Jo, Jinnam
    • International Journal of Reliability and Applications
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    • v.14 no.2
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    • pp.107-114
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    • 2013
  • Modelling of failures is an important element of reliability modelling. Empirical modelling approach suitable for complex item is explored in this paper. First step of the empirical modelling approach is to plot hazard function, density function, Weibull probability plot as well as cumulative intensity function to see which model fits best for the given data. Next step of the empirical modelling approach is select appropriate model for the data and fit the parametric model accordingly and estimate the parameters.

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Prediction of the Probability of Customer Attrition by Using Cox Regression

  • Kang, Hyuncheol;Han, Sang-Tae
    • Communications for Statistical Applications and Methods
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    • v.11 no.2
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    • pp.227-233
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    • 2004
  • This paper presents our work on constructing a model that is intended to predict the probability of attrition at specified points in time among customers of an insurance company. There are some difficulties in building a data-based model because a data set may contain possibly censored observations. In an effort to avoid such kind of problem, we performed logistic regression over specified time intervals while using explanatory variables to construct the proposed model. Then, we developed a Cox-type regression model for estimating the probability of attrition over a specified period of time using time-dependent explanatory variables subject to changes in value over the course of the observations.

On availability of Bayesian imperfect repair model

  • Cha, Ji-Hwan;Kim, Jae-Joo
    • Proceedings of the Korean Reliability Society Conference
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    • 2001.06a
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    • pp.301-310
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    • 2001
  • Lim et al.(1998) proposed the Bayesian Imperfect Repair Model, in which a failed system is perfectly repaired with probability P and is minimally repaired with probability 1 - P, where P is not fixed but a random variable with a prior distribution II(p). In this note, the steady state availability of the model is derived and the measure is obtained for several particular prior distribution functions.

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Bootstrap Confidence Intervals for a One Parameter Model using Multinomial Sampling

  • Jeong, Hyeong-Chul;Kim, Dae-Hak
    • Journal of the Korean Data and Information Science Society
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    • v.10 no.2
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    • pp.465-472
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    • 1999
  • We considered a bootstrap method for constructing confidenc intervals for a one parameter model using multinomial sampling. The convergence rates or the proposed bootstrap method are calculated for model-based maximum likelihood estimators(MLE) using multinomial sampling. Monte Carlo simulation was used to compare the performance of bootstrap methods with normal approximations in terms of the average coverage probability criterion.

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CHARACTERIZATIONS OF PARETO, WEIBULL AND POWER FUNCTION DISTRIBUTIONS BASED ON GENERALIZED ORDER STATISTICS

  • Ahsanullah, Mohammad;Hamedani, G.G.
    • Journal of the Chungcheong Mathematical Society
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    • v.29 no.3
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    • pp.385-396
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    • 2016
  • Characterizations of probability distributions by different regression conditions on generalized order statistics has attracted the attention of many researchers. We present here, characterization of Pareto and Weibull distributions based on the conditional expectation of generalized order statistics extending the characterization results reported by Jin and Lee (2014). We also present a characterization of the power function distribution based on the conditional expectation of lower generalized order statistics.