• International conference on construction engineering and project management
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• 2009.05a
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• pp.1223-1230
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• 2009

In the construction industry, Case-Based Reasoning (CBR) is considered to be the most suitable approach and determining the attribute weights is an important CBR problem. In this paper, a method is proposed for determining attribute weights that are calculated with attribute relation. The basic items of consideration were qualitative and quantitative influence factors. These quantitative factors were related to the qualitative factors to develop a Cost Drivers-structural equation model which can be used to estimate construction cost by considering attribute weight. The process of determining the attribute weight-structural equation model consists o 4 phases: selecting the predominant Cost Drivers for the SEM, applying the Cost Driers in the SEM, determining and verifying the attribute weights and deriving the Cost Estimation Equation. This study develops a cost estimating technique that complements the CBR method with a Cost Drivers-structural equation model which can be actively used during the schematic estimating phases of construction.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1199-1210
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• 2013

The high unemployment rate is one of the major problems in most countries nowadays. Hence, the demand for small area labor statistics has rapidly increased over the past few years. However, since sample surveys for producing official statistics are mainly designed for large areas, it is difficult to produce reliable statistics at the small area level due to small sample sizes. Most of existing studies about the small area estimation are related with the estimation of parameters based on cross-sectional data. By the way, since many official statistics are repeatedly collected at a regular interval of time, for instance, monthly, quarterly, or yearly, we need an alternative model which can handle this type of panel data. In this paper, we derive the generalized kernel estimating equation which can model time-dependency among response variables and handle repeated measurement or panel data. We compare the proposed estimating equation with the generalized linear model and the generalized estimating equation through simulation, and apply it to estimating the unemployment rates of 25 areas in Gyeongsangnam-do and Ulsan for 2005.

• Communications for Statistical Applications and Methods
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• v.23 no.4
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• pp.335-341
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• 2016

Interval censored failure time data often occurs in an observational study where a subject is followed periodically. Instead of observing an exact failure time, two inspection times that include it are made available. Several methods have been suggested to analyze interval censored failure time data (Sun, 2006). In this article, we are concerned with a binary time-varying covariate whose changing time is interval censored. A modified estimating equation is proposed by extending the approach suggested in the presence of a missing covariate. Based on simulation results, the proposed method shows a better performance than other simple imputation methods. ACTG 181 dataset were analyzed as a real example.

• Journal of Sericultural and Entomological Science
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• v.20 no.2
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• pp.36-39
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• 1978

With the current advances in insect toxicant bioassay, the need for easy methods of estimating the dosage-mortality regression equation has become vital. The Probit analysis seems to be not convenient for estimating the dosage-mortality regression equation and median lethal dose(LD50) because of its complexity in calculation. This study presents a comparision between Probit and Losit transformation for the estimation from bioassay results. Validation of the two methods is presented for the pathogenecity of nuclear polyhedrosis virus to the larva of fall web worm, Hyphantria cunea D.

• Journal of the Korean Statistical Society
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• v.36 no.3
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• pp.387-395
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• 2007

We propose a doubly robustified estimating function for the estimation of parameters in the context of ARCH models. We investigate asymptotic properties of estimators obtained as solutions of robust estimating equations. A simulation study shows that robust estimator from specified doubly robustified estimating equation provides better performance than conventional robust estimators especially under heavy-tailed distributions of innovation errors.

• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.207-216
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• 2011

Bootstrap is a resampling technique to find an estimate of parameters or to evaluate the estimate. This technique has been used in estimating parameters in linear model(LM) and generalized linear model(GLM). In this paper, we explore the possibility of applying Bootstrapping Residuals, Pairs, and an Estimating Equation that are most widely used in LM and GLM to the generalized estimating equation(GEE) algorithm for modelling repeatedly measured regression data sets. We compared three bootstrapping methods with coefficient and standard error estimates of GEE models from one simulated and one real data set. Overall, the estimates obtained from bootstrap methods are quite comparable, except that estimates from bootstrapping pairs are somewhat different from others. We conjecture that the strange behavior of estimates from bootstrapping pairs comes from the inconsistency of those estimates. However, we need a more thorough simulation study to generalize it since those results are coming from only two small data sets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1474-1480
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• 2013

This study attempted to estimate construction costs in accordance with the resource-based cost estimation (unit cost price) system by diameter for TBM method, and analyzed the direct cost and the total cost. Based on such figures, this study performed a regression analysis and proposed a model for an equation for estimating construction costs. model for the resource-based cost estimation (unit cost price) system classified by diameter for TBM method proposed by this study can be effectively applied to business planning, preliminary investigation, feasibility study, construction cost estimations in the early design stages.

• Water Engineering Research
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• v.5 no.4
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• pp.185-193
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• 2004

Estimates of annual actual evapotranspiration are needed in water balance studies, water resources management projects, and many different types of hydrologic studies. This study validated a set of 5 empirical equations of estimating annual actual evapotranspiration with climate data on 11 watersheds, and evaluated the further applicability of these forms in estimating annual runoff on watershed level. Five empirical equations generally overestimated annual evapotranspiration, with relative errors ranging $3.3\%$ to $47.2\%$. The results show that Schreiber formula can be applicable in determining annual evapotranspiration in sub-humid region that is classified by aridity index, while Zhang equation gave better results than the remaining methods in humid region. The mean differences for annual evapotranspiration bias over 11 watersheds are Zhang, Schreiber, Budyko, Pike, and Ol'dekop formula from lowest to highest. The empirical equations provide a practical tool to help water resources managers in estimating regional water resources on ungauged large watershed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.1022-1027
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• 2001

In this study, the train-induced vibration was measured at many locations at/around the actual service lines and the data base was constructed using the measurement results. The characteristics of train induced ground vibration was categorized and the empirical ground vibration estimating equations were developed. On the ground area (level grounds, embankments, cut sections), the vibration estimating equations were developed in terms of ground vibration level which was related with the distance from the source. Especially for the cut section areas, the vibration levels were expressed with the vibration receiving point expressed by the ratio of vertical distance to horizontal distance(V/H) from the source. As a result, when V/H is 0.96, the vibration estimating equation gives a minimum vibration level.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.207-214
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• 1999

Optimal estimating functions for a class of autoregressive models with GARCH(1,1) error are discussed. The asymptotic properties of the estimator as the solution of the optimal estimating equation are investigated for the models. We have also some simulation results which suggest that the proposed optimal estimators have smaller sample variances than those of the Conditional least-squares estimators under the heavy-tailed error distributions.