• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.1037-1046
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• 2003

We propose an equivariant and robust estimator in multivariate regression model based on the least trimmed squares (LTS) estimator in univariate regression. We call this estimator as multivariate least trimmed squares (MLTS) estimator. The MLTS estimator considers correlations among response variables and it can be shown that the proposed estimator has the appropriate equivariance properties defined in multivariate regression. The MLTS estimator has high breakdown point as does LTS estimator in univariate case. We develop an algorithm for MLTS estimate. Simulation are performed to compare the efficiencies of MLTS estimate with coordinatewise LTS estimate and a numerical example is given to illustrate the effectiveness of MLTS estimate in multivariate regression.

• Tunnel and Underground Space
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• v.22 no.2
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• pp.86-92
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• 2012

Point estimate method has a less accuracy than Monte Carlo simulation that is usually considered as an exact probabilistic method, but this method still remains popular in probability-based reliability assessment in geotechnical and rock engineering, because it significantly reduce the number of sampling points and produces the statistical moments of a performance function in a reasonable accuracy. In the present study, we investigated the accuracy and applicability of point estimate methods proposed by Rosenblueth and Zhou & Nowak by comparing the results of these two methods with those of Monte Carlo simulations. The comparison was carried out for the problem of a lined circular tunnel in an elastic medium where an closed-form analytical solution is given. The comparison results showed that despite the non-linearity of the analytical solution, the statistical moments calculated by the point estimate methods and the Monte Carlo simulations agreed well with an average error of roughly 1-2%. This average error demonstrates the applicability of the two point estimate methods for the probabilistic reliability assessment of underground structures in combination with numerical analysis.

• 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.

• Tunnel and Underground Space
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• v.12 no.3
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• pp.189-197
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• 2002

In recent years, the probabilistic analysis has been used in rock slope engineering. This is because uncertainty is pervasive in rock slope engineering and most geometric and geotechnical parameters of discontinuity and rock masses are involved with uncertainty. Whilst the traditional deterministic analysis method fails to properly deal with uncertainty, the probabilistic analysis has advantages quantifying the uncertainty in parameters. As a probabilistic analysis method, the Monte Carlo simulation has been used commonly. However, the Monte Carlo simulation requires many repeated calculations and therefore, needs much effort and time to calculate the probability of failure. In contrast, the point estimate method involves a simple calculation with moments for random variables. In this study the probability of failure in rock slope is evaluated by the point estimate method and the results are compared to the probability of failure obtained by Monte Carlo simulation method.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.225-232
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• 2009

Function Point Method have been applied to measure software size estimation in industry because it supports to estimate the software's size by user's view not developer's. However, the current function point method has some problems for example complexity's upper limit etc. So, In this paper, an enhanced function point model. Micro FP model, was suggested. Using this model, software effort estimation can be more efficiently because this model has some regression equation. This model specially can be applied to estimate in detail the large application system's size Analysis results show that measured software size by this Micro FP model has the advantage with more correlative between the one of LOC, as of 10 applications operated in an large organization.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.11
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• pp.1603-1609
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• 2006

To estimate undegraded intake protein (UIP) fraction in feeds and fodders, on the basis of their neutral detergent insoluble N content was studied. Samples of six feeds and forages were incubated in situ for a time equivalent to their mean retention time, estimated on the basis of their digestibility plus 10 h (to account for a lag in passage of particles from the rumen). The samples were incubated for 0, 25, 50, 75 and 100% of the estimated total mean retention time. UIP value of leguminous forages, obtained from the fractional rates of degradation and passage, were highly correlated with those estimated from samples incubated for 75% of total mean retention time, while incubating the non-leguminous forages and groundnut cake for this point over estimate the UIP fraction.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.2
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• pp.30-36
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• 2007

In order to estimate the maximum undeformed chip thickness in grinding operation, it is necessary to obtain the successive cutting point spacing. In the past it was obtained by experiments. In this paper, the average successive cutting point spacing has been obtained using the given grinding input conditions and it is possible to estimate the maximum undeformed chip thickness without using any experimentally obtained data. The validity of the proposed analysis has been verified based on two sets of grinding scratch tests using WA and CBN grinding wheels.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.163-178
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• 2001

We consider the experimental design problem of selecting values of design variables x for observation of a response y that depends on x and on model parameters $\theta$. The form of the dependence may be quite general, including all linear and nonlinear modeling situations. The goal of the design selection is to efficiently estimate functions of $\theta$. Three new criteria for selecting design points x are presented. The criteria generalized the usual Bayesian optimal design criteria to situations n which the prior distribution for $\theta$ amy be uncertain. We assume that there are several possible prior distributions,. The new criteria are applied to the nonlinear problem of designing to estimate the turning point of a quadratic equation. We give both analytic and computational results illustrating the robustness of the optimal designs based on the new criteria.

• Journal of Korean Society of Rural Planning
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• v.7 no.1 s.13
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• pp.77-88
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• 2001

In order to evaluate the applicability of GWLF model which can efficiently estimate non-point and point source pollutant loadings in rural watershed including urban district, the model was applied to an experimental watershed. The model was calibrated using observed data such as daily runoffs, sediment yields, T-N, and T-P. Simulated daily runoffs and sediment yields by the model using calibrated parameters were in food agreement with the observed data. There were difference between the simulated and observed nutrient loading which was considered resonable. The simulated results by the model showed that T-N, T-P and sediment yields were dependent on the amount of stream runoff discharge and land use. GWLF model is believed to applicable to estimate amount of pollutant loading of non-point source pollution for the water qualify control of agricultural watersheds.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.1
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• pp.18-27
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• 2020

In order to estimate the launch point of a high-speed vehicle, predicting the various characteristics of the vehicle's movement, such as drag and thrust, must be preceded by the estimation. To predict the various parameters regarding the vehicle's characteristics, we build the IMM filter specialized in predicting the parameters of the post-launch phase based on flight dynamics. Then we estimate the launch point of the high-speed vehicle using Inverse Dynamics. In addition, we assume the arbitrary error level of the radar for accuracy of the prediction. We organize multiple-dimensioned IMM structures, and figure out the optimal value of parameters by comparing the various IMM structures. After deriving the optimal value of parameters, we verify the launch point estimation error under certain error level.