• Communications for Statistical Applications and Methods
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• v.24 no.3
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• pp.271-290
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• 2017

We study a bivariate response regression model with arbitrary marginal distributions and joint distributions using Frank and Clayton's families of copulas. The proposed model is used for fitting dependent bivariate data with explanatory variables using the log-odd log-logistic Weibull distribution. We consider likelihood inferential procedures based on constrained parameters. For different parameter settings and sample sizes, various simulation studies are performed and compared to the performance of the bivariate odd-log-logistic-Weibull regression model. Sensitivity analysis methods (such as local and total influence) are investigated under three perturbation schemes. The methodology is illustrated in a study to assess changes on schoolchildren's oral health-related quality of life (OHRQoL) in a follow-up exam after three years and to evaluate the impact of caries incidence on the OHRQoL of adolescents.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.4
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• pp.401-407
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• 2021

To confirm the change of muzzle velocity and the most suitable probability distribution model of the 155 mm K9 howitzer barrel with chrome plating and changed rifling. Using a statistical program, the muzzle velocity were plotted on a normal distribution, a 2-parameter and 3-parameter Weibull distribution on a probability paper. Also, statistical parameters were estimated and muzzle velocity fitness test and probability of K676 charge were plotted. In both the chrome-plated with standard rifling and changed rifling for K9 barrel, the 2-parameter and 3-parameter Weibull distribution were skewed to the left compared to the normal distribution. It was confirmed that the muzzle velocity of the K9 barrel with chromium-plated is suitable for the normal distribution and 3-parameter Weibull distribution model.

• Wind and Structures
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• v.28 no.1
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• pp.63-70
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• 2019

Due to developing environmental concern use of renewable energy source is very essential. The great demand for the energy supply coupled with inadequate energy sources creates an emergency to find a new solution for the energy shortage. The appropriate wind energy distribution is the fundamental requirement for the assessment of wind energy potential available at the particular site essential for the design of wind farms. Hence the proper specification of the wind speed distribution plays a vital role. In this paper the Bimodal Weibull distribution is used to estimate the Capacity factor at the proposed site. The shape and scale parameters estimated using Maximum likelihood method is used as the initial value for extrapolation. Application of this model will give an accurate result overwhelming the concept of overestimation or underestimation of Capacity factor.

• Journal of Korean Society on Water Environment
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• v.31 no.2
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• pp.142-150
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• 2015

The relationship between the number of benthic macroinvertebrate species and the accumulated survey area were investigated in a clean stream and an impaired stream of Korea. Five models to characterize species-area functions were compared, and the Weibull model fitted species-area data well. The other models (Arrhenius, Romell-Gleason, Kylin, Lognormal model) had small or notable bias. The maximum number of species and half-saturation area derived from the Weibull model may be used as the indicators of the carrying capacity and the habitat complexity respectively.

• Wind and Structures
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• v.31 no.4
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• pp.311-319
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• 2020

India is a developing nation and heavily spends on the development of wind power plants to meet the national energy demand. The objective of this paper is to investigate wind power potential of Ennore site using wind data collected over a period of two years by three parameter Weibull distribution. The Weibull parameters are estimated using maximum likelihood, least square method and moment method and the accuracy is determined using R² and root mean square error values. The site specific capacity factor is calculated by the mathematical model developed by three parameter Weibull distribution at different hub heights above the ground level. At last, the wind energy economic analysis is carried out using capacity factor at 30 m, 40 m and 50 m height for different wind turbine models. The analysis showed that the site has potential to install utility wind turbines to generate energy at the lowest cost per kilowatt-hour at height of 50 m. This research provides information of wind characteristics of potential sites and helps in selecting suitable wind turbine.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.643-653
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• 2013

The most important procedure in frequency analysis is to determine the appropriate probability distribution and to estimate quantiles for a given return period. To perform the frequency analysis, the goodness-of-fit tests should be carried out for judging fitness between obtained data from empirical probability distribution and assumed probability distribution. The previous goodness-of-fit could not consider enough extreme events from the recent climate change. In this study, the critical values of the modified Anderson-Darling test statistics were derived for 3-parameter Weibull distribution and power test was performed to evaluate the performance of the suggested test. Finally, this method was applied to 50 sites in South Korea. The result shows that the power of modified Anderson-Darling test has better than other existing goodness-of-fit tests. Thus, modified Anderson-Darling test will be able to act as a reference of goodness-of-fit test for 3-parameter Weibull model.

• Water for future
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• v.10 no.1
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• pp.79-94
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• 1977

This study is aimed at the establishment and examination of stochastic model to simulate Run-length and Run-sum of daily rainfall and streamflow. In the analysis, daily rainfall records in major cities (Seoul, Kangnung, Taegu, Kwangju, Busan, and Cheju) and daily streamflow records of Major rivers (Han, Nakdong and Geum River) were used. Also, the fitness of daily rainfall and streamflow to Weibull and one parameter exponential distribution was tested by Chi-square and Kolmogorov-Smirnov test, from which it was found that daily rainfall and streamflow generally fit well to exponential type distribution function. The Run-length and Run-sum were simulated by the Weibull Model (WBL Model), one parameter exponential model (EXP-1 Model) based on the Nonte Carlo technique. In this result, Run-length of rainfall was fitted for one parameter exponential model and Run-length of streamflow was fitted for Weibull model. And Run-sum of rainfall and streamflow were fit comparatively for regression model. Hereby, statistical charactristics of Simulation data were sinilar to historical data.

• Industrial Engineering and Management Systems
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• v.6 no.1
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• pp.1-10
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• 2007

The objective of this study is to develop an optimal joint cost from the perspectives of both the manufacturer and the retailer. The integrated production-inventory model with Weibull distribution deteriorating items is assumed to have a constant demand rate. A limited retailer storage space and multiple delivery per order are considered in this model. A numerical example including the sensitivity analysis is given to validate the results of the production-inventory model.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.159-168
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• 2008

A special field experiment has been carried out from March 2001 to June 2001 at the Changhowon in Kyunggi to investigate a better methodology for the estimation of dry deposition of pollutions applicable in Korea. In this study, dry deposition plate was used to measure of total and water soluble acidic mass fluxes, and CPRI(Coarse Particle Rotary Impactor), CI(Cascade Impactor) were also used to measure ambient concentrations in various particle size ranges. Sehmel-Hodgson model was used to estimate dry depostion velocity and Weibull probability distribution function was applied to get generalized particle size distribution for the size fractioned concentration data sampled by CPRI and CI. Atmospheric dry deposition fluxes of mass and ionic matters estimated by the various techniques(one-step, multi-step, equi-concentration, subdivision for only the coarse particle range, applying Weibull distribution function, etc.) were compared to flux data sampled by DDP. It was found out that the deposition fluxes estimation methodology calculated by the each particle size range devided by particle size distribution characteristics and the rapidly changed points of deposition velocity using Weibull probability distribution function was the most applicable.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.1829-1831
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• 2012

Background: The generalized gamma distribution statistics constitute an extensive family that contains nearly all of the most commonly used distributions including the exponential, Weibull and log normal. A saturated version of the model allows covariates having effects through all the parameters of survival time distribution. Accelerated failure-time models assume that only one parameter of the distribution depends on the covariates. Methods: We fitted both the conventional GG model and the saturated form for each of its members including the Weibull and lognormal distribution; and compared them using likelihood ratios. To compare the selected parameter distribution with log logistic distribution which is a famous distribution in survival analysis that is not included in generalized gamma family, we used the Akaike information criterion (AIC; r=l(b)-2p). All models were fitted using data for 369 women age 50 years or more, diagnosed with stage IV breast cancer in BC during 1990-1999 and followed to 2010. Results: In both conventional and saturated parametric models, the lognormal was the best candidate among the GG family members; also, the lognormal fitted better than log-logistic distribution. By the conventional GG model, the variables "surgery", "radiotherapy", "hormone therapy", "erposneg" and interaction between "hormone therapy" and "erposneg" are significant. In the AFT model, we estimated the relative time for these variables. By the saturated GG model, similar significant variables are selected. Estimating the relative times in different percentiles of extended model illustrate the pattern in which the relative survival time change during the time. Conclusions: The advantage of using the generalized gamma distribution is that it facilitates estimating a model with improved fit over the standard Weibull or lognormal distributions. Alternatively, the generalized F family of distributions might be considered, of which the generalized gamma distribution is a member and also includes the commonly used log-logistic distribution.