• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.797-805
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• 2012

Many circular distributions are known to be not only asymmetric but also bimodal. Hidden truncation method of generating asymmetric distribution is applied to a bivariate circular distribution to generate an asymmetric circular distribution. While many other existing asymmetric circular distributions can only model an asymmetric data, this new circular model has great flexibility in terms of asymmetry and bi-modality. Some properties of the new model, such as the trigonometric moment generating function, and asymptotic inference about the truncation parameter are presented. Simulation and real data examples are provided at the end to demonstrate the utility of the novel distribution.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.581-589
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• 2005

The purpose of this thesis is to develop and introduce Add-in program which we can systematically, visually and dynamically study discrete probability distribution of binomial distribution, poisson distribution and hypergeometric distribution, and continuous probability distribution of normal distribution, exponential distribution, and the definition and characteristics of t distribution, F distribution and ${\chi}^2$ distribution to be driven from normal distribution, and graphs, the computation process of probability by using VBA which is the device of Excel.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.923-931
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• 2005

The two parameter generalized exponential distribution was recently introduced by Gupta and Kundu (1999). It is observed that the generalized exponential distribution can be used quite effectively to analyze skewed data set. This paper develops the accelerated life test model using generalized exponential distribution and considers maximum likelihood estimation of parameters under the tampered random variable model. To show the performance of proposed maximum likelihood estimates, some simulation will be performed. Using a real data set, an example will be given.

• International Journal of Reliability and Applications
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• v.8 no.1
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• pp.17-25
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• 2007

Maximum likelihood method is utilized to estimate the two parameters of generalized exponential distribution based on grouped and censored data. This method does not give closed form for the estimates, thus numerical procedure is used. Reliability measures for the generalized exponential distribution are calculated. Testing the goodness of fit for the exponential distribution against the generalized exponential distribution is discussed. Relevant reliability measures of the generalized exponential distributions are also evaluated. A set of real data is employed to illustrate the results given in this paper.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.265-276
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• 2015

In this paper, we propose hierarchical cluster analysis and multidimensional scaling for joint distribution valued data. Information technology is increasing the necessity of statistical methods for large and complex data. Symbolic Data Analysis (SDA) is an attractive framework for the data. In SDA, target objects are typically represented by aggregated data. Most methods on SDA deal with objects represented as intervals and histograms. However, those methods cannot consider information among variables including correlation. In addition, objects represented as a joint distribution can contain information among variables. Therefore, we focus on methods for joint distribution valued data. We expanded the two well-known exploratory methods using the dissimilarities adopted Hall Type relative projection index among joint distribution valued data. We show a simulation study and an actual example of proposed methods.

• Journal of Industrial Technology
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• v.15
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• pp.41-50
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• 1995

This paper presents a technique for estimating distribution of data stored in a database. This technique is very useful for accurate selectivity estimation, which is essential in query optimization and physical database design. To maintain data distribution, we employ the directory of the multilevel grid file, a multidimensional dynamic file organization. The major advantage of our technique is that data distribution information is maintained dynamically in the multilevel grid file. In contrast, other static methods such as the histogram method use static date structures, which requires periodic restructuring. Furthermore, we propose a method for keeping the abstract information of data distribution in main memory. This is advantageous in the situation where the size of main memory is not sufficient. Finally, We also suggest formulas for calculating selectivies of various queries based on our data distribution information.

• Journal of Applied Reliability
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• v.2 no.2
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• pp.63-83
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• 2002

Degradation data can provide more reliability information than traditional failure-time data, especially products with few or no failures. This paper is concerned with a method of estimating lifetime distribution from field data with supplementary information on degradation data and covariates. When a distribution of degradation rate obtained by follow-up study for a portion of products that survive after-warranty follows a reciprocal-Weibull or lognormal distribution. A time-to-failure distribution of the product follows Weibull or lognormal distribution, respectively. A method of estimating lifetime parameters for this kind of data and their asymptotic properties are studied. Effects of after-warranty report probability, follow-up rate, and proportion of degradation data on pseudo maximum likelihood estimators of these parameters are investigated.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.338-343
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• 1998

This study is to select appropriate probability distributions for ten days evaporation data for the purpose of representing statistical characteristics of real evaporation data in Korea. Nine probability distribution functions were assumed to be underlying distributions for ten days evaporation data of 20 stations with the duration of 20 years. The parameter of each probability distribution function were estimated by the maximum likelihood approach, and appropriate probability distributions were selected from the goodness of fit test. Log Pearson type III model was selected as an appropriate probability distribution for ten days evaporation data in Korea.

• Journal of the Korean Ceramic Society
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• v.34 no.9
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• pp.927-934
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• 1997

Static and cyclic fatigue tests were carried out for alumina specimen to study the statistical analyses (normal, lognormal and Weibull distribution) of fatigue lifetime data and nominal initial crack length data. Fatigue lifetime data followed Weibull distribution better than normal or lognormal distribution, for the shape parameter of the notched specimen was larger than that of the unnotched specimen. The nominal initial crack length data obtained from fatigue lifetime followed the lognormal and Weibull distribution better than normal distribution, for the coefficient of variation of the unnotched specimen was larger than that of the notched specimen, and shape parameter of unnotched specimen was smaller than that of the notched specimen.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.1
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• pp.108-117
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• 2017

This paper presents a distribution simulation model for dual purpose improved conventional munitions based on flight test data. A systematic procedure for designing a dispersion simulation model is proposed. A new accumulated broken line graph was suggested for designing the distribution shape. In the process of verification and simulation for the distribution simulation model, verification was performed by first comparing data with firing test results, and an application simulation was then conducted. The Monte Carlo method was used in the simulations, which reflected the relationship between ejection conditions and real distribution data. Before establishing the simulation algorithm, the dominant ejection parameter of the submunitions was examined. The relationships between ejection conditions and distribution results were investigated. Five key distribution parameters were analyzed with respect to the ejection conditions. They reflect the characteristics of clustered particle dynamics and aerodynamics.