• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.55-64
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• 2024

In this study, we consider the sample size determination problem for clustered count data with many zeros. In general, zero-inflated Poisson and binomial models are commonly used for zero-inflated data; however, in real data the assumptions that should be satisfied when using each model might be violated. We calculate the required sample size based on a discrete Weibull regression model that can handle both underdispersed and overdispersed data types. We use the Monte Carlo simulation to compute the required sample size. With our proposed method, a unified model with a low failure risk can be used to cope with the dispersed data type and handle data with many zeros, which appear in groups or clusters sharing a common variation source. A simulation study shows that our proposed method provides accurate results, revealing that the sample size is affected by the distribution skewness, covariance structure of covariates, and amount of zeros. We apply our method to the pancreas disorder length of the stay data collected from Western Australia.

• Journal of applied mathematics & informatics
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• v.42 no.1
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• pp.179-187
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• 2024

In the Quality Control and inspection processes, the use of attribute sampling strategies is crucial. In this study, we incorporate the neutrosophic fuzzy acceptance sampling plan method to present a fresh approach to attribute sampling plans. Utilizing the benefits of neutrosophic fuzzy sets, the proposed sampling plan method models and assesses the acceptance standards for attribute sampling. We compare the suggested method to already-in-use attribute sampling techniques plans with new attribute six sigma sampling techniques plan is proposed in order to verified its efficacy. The outcomes show the neutrosophic fuzzy acceptance sampling plan's superiority in terms of its capacity to manage uncertainties, account for ambiguity, and produce more precise quality evaluation outputs.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1110-1116
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• 2008

In this paper, we suggest GP operators based on tree structure considering tree distributions in structure space and structural difficulties. The main idea of the proposed genetic operators is to place generated offspring into the specific region which nodes and depths are balanced and most of solutions exist. To enable that, the proposed operators are designed to utilize region information where parents belong and node/depth rates of selected subtree. To demonstrate the effectiveness of our proposed approach, experiments of binomial-3 regression, multiplexer and even parity problem are executed. The experiments results show that the proposed operators based on tree structure is superior to the results of standard GP for all three test problems in both success rate and number of evaluations.

• Management Science and Financial Engineering
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• v.16 no.1
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• pp.119-135
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• 2010

In this paper, we readdress the optimization problem for minimizing the inspection cost in a back-light unit inspection system, which forms a network including a K-stage inspection system, a source inspection shop, and a re-inspection shop. In order to formulate our objective function when the system is in a steady state, assuming that the number of nonconforming items in a lot follows a binomial distribution when a lot is formed for inspection, we make a steady-state network flow analysis between shops, and derive the steady-state amount of flows between nodes and the steady-state fraction defectives by solving a nonlinear balance equation. Finally we provide some fundamental properties and an enumeration method for determining an optimal value of K which minimizes our objective function. In addition, we compare our results numerically with previous ones.

• Communications of the Korean Mathematical Society
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• v.14 no.4
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• pp.789-795
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• 1999

Let $A_1$,A$_2$…, A\ulcorner and B$_1$,B$_2$…, B\ulcorner be two sequences of events on the same probability space. Let X= X\ulcorner(A) and Y-Y\ulcorner)(B), repectively, by the number of those A\ulcorner and B\ulcorner which oc-cur. We establish bivariate lower bounds on the distribution P(X$\geq$1, Y, $\geq$1)and P(X$\geq$i , $Y\geq$j)by linear combinations of the bino-mial moments S\ulcorner, \ulcorner, 1$\leq$i$\leq$j

• Communications for Statistical Applications and Methods
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• v.25 no.2
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• pp.173-184
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• 2018

In medical or public health research, it is common to encounter clustered or longitudinal count data that exhibit excess zeros. For example, health care utilization data often have a multi-modal distribution with excess zeroes as well as a multilevel structure where patients are nested within physicians and hospitals. To analyze this type of data, zero-inflated count models with mixed effects have been developed where a count response variable is assumed to be distributed as a mixture of a Poisson or negative binomial and a distribution with a point mass of zeros that include random effects. However, no study has considered a situation where data are also censored due to the finite nature of the observation period or follow-up. In this paper, we present a weighted version of zero-inflated Poisson model with random effects accounting for variable individual follow-up times. We suggested two different types of weight function. The performance of the proposed model is evaluated and compared to a standard zero-inflated mixed model through simulation studies. This approach is then applied to Medicaid data analysis.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1636-1638
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• 2012

주식시장에서 개별 종목의 등락을 예측하는 것은 불가능하다. 미래가 정해져 있다면 그것을 아는 순간 거래는 성립되지 않기 때문이다. 따라서 개별 종목의 등락은 기업의 가치뿐만 아니라 투자참여자의 수급에 의해서 결정되므로 등락 확률은 예측불가인 0.5에 가깝다. 따라서 개별종목의 총합인 종합지수 역시 예측이 불가능해도 확률적인 틀은 제시할 수 있다. 바이노미알 분포를 사용하여 n을 충분히 증가시키면 가우시안 분포가 되고 이를 이동평균선으로 지표화한 Bollinger Band를 이용하는 것이다. 중심선에 480일선을 상하한폭을 $2{\sigma}$, $4{\sigma}$로 하여 그 틀을 제시하고, 이를 주요 종합지수로 검증하였다.

• Water for future
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• v.26 no.3
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• pp.113-124
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• 1993

This study aims at the evaluation of the stationary distribution and the emptiness passage time for the effectiveness of water utility in the Keumgang estuary reservoir by two-step transition model. It was taken discrete Markovian correlated inflows for the joint probability of inflows and storage, and was used binomial distribution for inflows distribution. As the results, it was decreased from 0.952 to 0.904 the emptiness probability of the reservoir stationary distribution during 1952-1980, and from 0.900 to 0.829 during 1981-1989, and the average emptiness passage time was increased from 23 days to 37 days during 1952-1980, and from 29 days to 61 days during 1981-1989 at low state of storage. From this, it is found that the emptiness passage time is varied with the increase of the inflows auto-correlation coefficient in the Keumgang estuary reservoir. Therefore, it is understood that auto-correlation coefficient must be taken into consideration for the evaluation of water utility in a small reservoir at drought time.

• Journal of Global Scholars of Marketing Science
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• v.11
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• pp.129-146
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• 2003

This study explores whether a NBD type of model can be applied to characterize the underlying frequency distribution of online consumer's visit behavior. In this study, the following two research questions are addressed: (1) How can we characterize the underlying distribution pattern(s) of the number of repeat i i visits to a site? (2) How can consumer's Internet usages and his/her demographics affect the average number of visits to the site? Through the empirical investigation, this study found that NBD models are directly applicable to characterize the underlying distribution of visit frequency on the Internet. Furthermore, this study addresses some managerial implications for understanding how site visits are determined. Especially this study highlights the relationship between repeated visits and the visitors' Internet Usages and demographics. The proposed models are estimated and validated by online panel data that covers more than 1000 different sites and has 800,000 observations.