• Journal of the Korean Society of Safety
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• v.30 no.1
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• pp.52-59
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• 2015

The aim of the paper is to introduce the statistical definition of the specified compressive strength of the concrete to be used for safety evaluation of the existing structure in domestic practice and to present the practical method to obtain the specified strength by utilizing the non-destructive test data as well as the limited number of core test data. The statistical definition of the specified compressive strength of concrete in the design codes is reviewed and the consistent formulations to statistically estimate the specified strength for assessment are described. In order to prevent estimating an unrealistically small value of the specified strength due to limited number of data, it is proposed that the information from the non-destructive test data is combined to that of the minimum core test data. The the sample mean, standard deviation and total number of concrete test are obtained from combined test data. The proposed procedures are applied to an example test data composed of the artificial numerical values and the actual evaluation data collected from the bridge assessment reports. The calculation results show that the proposed statistical estimation procedures yield reasonable values of the specified strength for assessment by applying the non-destructive test data in addition to the limited number of core test data.

• Journal of Ocean Engineering and Technology
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• v.23 no.6
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• pp.71-76
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• 2009

This paper describes a statistical analysis method for predicting a coast fishing boat's effective horsepower. The EHP estimation method for small coast fishing boats was developed, based on a statistical regression analysis of model test results in a circulating water channel. The statistical regression formula of a fishing boat's effective horsepower is determined from the regression analysis of the resistance test results for 15 actual coast fishing boats. This method was applied to the effective horsepower prediction of a G/T 4 ton class coast fishing boat. From the estimation of the effective horsepower using this regression formula and the experimental model test of the G/T 4 ton class coast fishing boat, the estimation accuracy was verified under 10 percent of the design speed. However, the effective horsepower prediction method for coast fishing boats using the regression formula will be used at the initial design and hull-form development stage.

• International Journal of Highway Engineering
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• v.18 no.1
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• pp.1-11
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• 2016

PURPOSES : This study estimated the load effect of a single heavy truck to develop a live load model for the design and assessment of bridges located on an expressway with a limited truck entry weight. METHODS : The statistical estimation methods for the live load effect acting on a bridge by a heavy vehicle are reviewed, and applications using the actual measurement data for trucks traveling on an expressway are presented. The weight estimation of a single vehicle and its effect on a bridge are fundamental elements in the construction of a live load model. Two statistical estimation methods for the application of extrapolation in a probabilistic study and an additional estimation method that adopts the extreme value theory are reviewed. RESULTS : The proposed methods are applied to the traffic data measured on an expressway. All of the estimation methods yield similar results using the data measured when the weight limit has been relatively well observed because of the rigid enforcement of the weight regulation. On the other hand, when the estimations are made using overweight traffic data, the resulting values differ with the estimation method. CONCLUSIONS : The estimation methods based on the extreme distribution theory and the modified procedure presented in this paper can yield reasonable values for the maximum weight of a single truck, which can be applied in both the design and evaluation of a bridge on an expressway.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.615-624
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• 2015

We consider the estimation of seasonal cointegration in the presence of conditional heteroskedasticity (CH) using a feasible generalized least squares method. We capture cointegrating relationships and time-varying volatility for long-run and short-run dynamics in the same model. This procedure can be easily implemented using common methods such as ordinary least squares and generalized least squares. The maximum likelihood (ML) estimation method is computationally difficult and may not be feasible for larger models. The simulation results indicate that the proposed method is superior to the ML method when CH exists. In order to illustrate the proposed method, an empirical example is presented to model a seasonally cointegrated times series under CH.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.637-645
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• 2003

Small area estimation had been studied using data-based methods such as Direct, Indirect, Synthetic methods. However recently, model-based such as based on regression or time series estimation methods are applied to the study. In this paper we investigate a model-data based small area estimation which takes into account the spatial relation among the areas. The Economic Active Population Survey in 2001 are used for analysis and the results from the model based and model-data based estimation are compared with using MSE(Mean squared error), MAE(Mean absolute error) and MB(Mean bias).

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.75-86
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• 1999

An air-data estimator for generic air-breathing hypersonic vehicles (AHSVs) is developed and demonstrated with an example vehicle configuration. The AHSV air-data estimation strategy emphasized improvement of the angle of attack estimate accuracy to a degree necessitated by the stringent operational requirements of the air-breathing propulsion. the resulting estimation problem involves highly nonlinear diffusion process (propagation); consequently, significant distortion of a posteriori conditional density is suspected. A simulation based statistical analysis tool is developed to characterize the nonlinear diffusion process. The statistical analysis results indicate that the diffusion process preserves the symmetry and unimodality of initial probability density shape state variables, and provide the basis for applicability of an Extended Kalman Filter (EKF). An EKF is designed for the AHSV air-data system and the air data estimation capabilities are demonstrated.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.3
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• pp.413-422
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• 2000

In the class of models which include random effects, the variance component estimates are important to obtain accurate predictors and estimators. Variance component estimation is straightforward for balanced data but not for unbalanced data. Since orthogonality among factors is absent in unbalanced data, various methods for variance component estimation are available. REML estimation is the most widely used method in animal breeding because of its attractive statistical properties. Recently, Bayesian approach became feasible through Markov Chain Monte Carlo methods with increasingly powerful computers. Furthermore, advances in variance component estimation with complicated models such as generalized linear mixed models enabled animal breeders to analyze non-normal data.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.73-85
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• 2001

The spatial population existing in a plane ares, such as an animal or aerial population, have certain relationships among regions which are located within a fixed distance from one selected region. We consider with the adaptive searching estimation in spatial sampling for a spatial population. The adaptive searching estimation depends on values of sample points during the survey and on the nature of the surfaces under investigation. In this paper we study the estimation by the adaptive searching in a spatial sampling for the purpose of estimating the area possessing a particular characteristic in a spatial population. From the viewpoint of adaptive searching, we empirically compare systematic sampling with stratified sampling in spatial sampling through the simulation data.

• Current Optics and Photonics
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• v.1 no.5
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• pp.551-555
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• 2017

Tissue optics is a well-established and extensively studied area. In the last decades, Monte Carlo simulation (MCS) has been one of the standard tools for simulation of light propagation in turbid media. The utilization of parallel processing exhibits dramatic increase in the speed of MCS's of photon migration. Some calculations based on MCS can be completed within a few seconds. Since the MCS's have the potential to become a real time calculation method, a dynamic accuracy estimation, which is also known as history by history statistical estimators, is required in the simulation code to automatically terminate the MCS as the results' accuracy achieves a high enough level. In this work, spatial and time-domain GPU-based MCS, adopting the dynamic accuracy estimation, are performed to calculate the light dose/reflectance in homogeneous and heterogeneous tissue media. This dynamic accuracy estimation can effectively derive the statistical error of optical dose/reflectance during the parallel Monte Carlo process.

• Communications for Statistical Applications and Methods
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• v.28 no.6
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• pp.627-641
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• 2021

An asymmetric least squares estimation method has been employed to estimate linear models for percentile regression. An asymmetric maximum likelihood estimation (AMLE) has been developed for the estimation of Poisson percentile linear models. In this study, we propose generalized nonlinear percentile regression using the AMLE, and the use of the parametric bootstrap method to obtain confidence intervals for the estimates of parameters of interest and smoothing functions of estimates. We consider three conditional distributions of response variables given covariates such as normal, exponential, and Poisson for three mean functions with one linear and two nonlinear models in the simulation studies. The proposed method provides reasonable estimates and confidence interval estimates of parameters, and comparable Monte Carlo asymptotic performance along with the sample size and quantiles. We illustrate applications of the proposed method using real-life data from chemical and radiation epidemiological studies.