• Journal of Korean Society for Quality Management
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• v.24 no.2
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• pp.25-43
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• 1996

This paper presents the optimal and practical constant-stress accelerated life test plans for the lognormal lifetime distribution tinder assumptions of intermittent inspection and Type-I censoring. In an optimal plan, the low stress level and the proportions of test units allocated at each stress are determined under given inspection scheme and number of inspections such that the asymptotic variance of the maximum likelihood estimator of a certain quantile at use condition is minimized. Although the practical plan adopts the same design criterion, it involves three rather than two overstress levels in order to compromise the practical deficiencies of the optimal plan. Computational experiments are conducted to choose an allocation plan and a inspection scheme of the practical plan and to compare with test plans over a range of parameter values.

• Journal of the Korean Data and Information Science Society
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• v.7 no.1
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• pp.47-57
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• 1996

This paper on planning constant accelerated life test is assumed that parameters for a lognormal life distribution are depended on changes of stresses. The proposed test plans are optimum in that they minimize the asymptotic variance of maximum likelihood estimator of a specified quantile at the design stress. The optimal amount of low stress level ${\xi}_{L}$ and optimal sample proportion ${\pi}$ to be allocated at low stress level are obtained when the ratio of scales at high stress level and design stress level is unknown.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.493-505
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• 2017

Maximum likelihood estimation (MLE) of the generalized extreme value distribution (GEVD) is known to sometimes over-estimate the positive value of the shape parameter for the small sample size. The maximum penalized likelihood estimation (MPLE) with Beta penalty function was proposed by some researchers to overcome this problem. But the determination of the hyperparameters (HP) in Beta penalty function is still an issue. This paper presents some data adaptive methods to select the HP of Beta penalty function in the MPLE framework. The idea is to let the data tell us what HP to use. For given data, the optimal HP is obtained from the minimum distance between the MLE and MPLE. A bootstrap-based method is also proposed. These methods are compared with existing approaches. The performance evaluation experiments for GEVD by Monte Carlo simulation show that the proposed methods work well for bias and mean squared error. The methods are applied to Blackstone river data and Korean heavy rainfall data to show better performance over MLE, the method of L-moments estimator, and existing MPLEs.

• Journal of Distribution Science
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• v.11 no.7
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• pp.5-13
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• 2013

Purpose - The study explores social well-being of the community of five selected countries of the South Asia: India, Pakistan, Sri Lanka, Nepal and Bangladesh. The study compares effectiveness of macroeconomic policies across the countries through interactive effects of the macroeconomic policy variables with the regional dummy variables. Research design, data, and methodology - Using the data set for the period of 1990-2008, this study employs panel data models, quantile regression methods, and the fixed effects method, which the constant is treated as group or country-specific. The model can also be known as the least-squares dummy variables estimator. Results - The results reveal significant chances of improvement in the well-being of the people while living in India and Pakistan as compared to the other countries of the region where India relatively stands with better chances of providing opportunities to improve the well-being of the people. Conclusions - This study recommends an increasing allocation of budget on education and health in order to enhance social well-being in the South Asian region. Inflation is the main cause of deteriorating well-being of the South Asian community by escalating the cost of living. Comprehensive study is recommended by employing the micro data models in the region.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.151-163
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• 2018

The objective of this study was to estimate LOADEST (LOAD Estimator) coefficients for simulating pollutant loads in ungauged watersheds. Regression models of LOADEST were used to simulate pollutant loads, and the multiple linear regression (MLR) was used for coefficients estimation on watershed characteristics. The fifth and third model of LOADEST were selected to simulate T-N (Total-Nitrogen) and T-P (Total-Phosphorous) loads, respectively. The results and statistics indicated that regression models based on LOADEST simulated pollutant loads reasonably and model coefficients were reliable. However, the results also indicated that LOADEST underestimated pollutant loads and had a bias. For this reason, simulated loads were corrected the bias by a quantile mapping method in this study. Corrected loads indicated that the bias correction was effective. Using multiple regression analysis, a coefficient estimation methods according to the watershed characteristic were developed. Coefficients which calculated by MLR were used in models. The simulated result and statistics indicated that MLR estimated the model coefficients reasonably. Regression models developed in this study would help simulate pollutant loads for ungauged watersheds and be a screen model for policy decision.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.129-138
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• 2019

Ammunition is an integral element of a weapon systems and in calculating fighting strength. The Korea Army utilizes the basic load (B/L) concept to supply ammunition smoothly. The required supply rate (RSR) is the basis of a B/L that is estimated from real combat data that includes a troop's mission and operation terrain. The current RSR is based on Korean War data and the sample mean has some problems in applications to modern combat. Therefore, this study used Korea Combat Training Center (KCTC) data that is similar to real combat to estimate rifle ammunition RSR. We used a quantile of truncated Weibull distribution to estimate rifle ammunition RSR considering that rifle ammunition consumption data in KCTC is truncated. As a result, we obtained a rifle ammunition RSR which covers most ammunition consumption by reflecting the individual consumption of rifle ammunition.