• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.935-944
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• 1998

This paper investigates the problem of goodness of fit tests for no effect model. The proposed test statistic $Z_{mn}$ is obtained by multiplying constant on the model free curve estimation techniques. The small and large sample properties of$Z_{mn}$ are investigated and the good results of power studies for the proposed test are illustrated.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.967-976
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• 2011

The Box-Cox transformation is a well known family of power transformations that brings a set of data into agreement with the normality assumption of the residuals and hence the response variable of a postulated model in regression analysis. Normalization (studentization) of the regressors is a common practice in analyzing microarray data. Here, we implement Box-Cox transformation in normalizing regressors in microarray data. Pridictabilty of the model can be improved using data transformation compared to studentization.

• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.459-468
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• 2002

A class of asymmetric beta-ARCH processes is proposed and connections to traditional ARCH models are explained. Geometric ergodicity of the model is discussed. Conditional least squares as well as maximum likelihood estimators of parameters and their limit results are also presented. A test for symmetry of the model is studied with limiting power of test statistic given.

• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.71-82
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• 2001

There are several ways to test the equality of two survival distributions under a variety of situations. Tests for equality of two distributions with life-table model for univariate independent response times are reviewed and introduced. It is developed that the methodology to test it for correlated response times where treatments are applied to different independent sets of cohorts. Data, which can be separated into two independent sets, from an angioplasty study where more than one procedure is performed on some patients are used to illustrate this methodology.

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.25-33
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• 1998

We review a multivariate version of Kendall's tau based on direction vectors of observations. And with this statistic we propose an analog of the forward variable selection method which selects a set of independent variables for further studies to build the eventual predicting model. This method does not assume the distributions of observations and the linear model and it is strong to the outliers with high asymptotic efficiencies relative to the parametric Pearson's correlation coefficient.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4A
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• pp.343-352
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• 2010

Recently, many researchers have been carried out to estimate more controlled service life and long-term performance of carbonated concrete structures. Durability analysis and design based on probability have been induced to new concrete structures for design. This paper provides a carbonation prediction model based on the Fick's 1st law of diffusion using statistic data of carbonated concrete structures and the probabilistic analysis of the durability performance has been carried out by using a Bayes' theorem. The influence of concerned design parameters such as $CO_2$ diffusion coefficient, atmospheric $CO_2$ concentration, absorption quantity of $CO_2$ and the degree of hydration was investigated. Using a monitoring data, this model which was based on probabilistic approach was predicted a carbonation depth and a remaining service life at a variety of environmental concrete structures. Form the result, the application method using a realistic carbonation prediction model can be to estimate erosion-open-time, controlled durability and to determine a making decision for suitable repair and maintenance of carbonated concrete structures.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.2
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• pp.79-89
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• 2003

A research about finding a new electricity load model that is sensitive to the price of electricity is conducted. This new model i5 polynomial type price sensitive electricity consumption model, while former electricity consumption models have exponential terms or statistic terms. The pattern of electricity consumption of each electricity using devices were identified first, then the proportion of the devices at buses or nodes are investigated, finally weighted sum of electricity consumption and the proportion makes the load model or consumption model of electricity at one bus or node. This new model is easy to use in the simulations or calculations of the electricity consumption, because the arithmetic of functions with polynomial terms are easy compared to the functions with transcendental terms.

• Journal of the Korean Statistical Society
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• v.25 no.3
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• pp.433-444
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• 1996

In contrast to the multiplicative risk model, the additive risk model specifies that the hazard function with covariates is the sum of, rather than product of, the baseline hazard function and the regression function of covariates. We, in this paper, propose a method for checking the adequacy of the additive risk model based on partial-sum of matingale residuals. Under the assumed model, the asymptotic properties of the proposed test statistic and approximation method to find the critical values of the limiting distribution are studied. Several real examples are illustrated.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2B
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• pp.163-171
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• 2009

Classical linear models have been generally used to analyze and forecast hydrologic time series. However, there is growing evidence of nonlinear structure in natural phenomena and hydrologic time series associated with their patterns and fluctuations. Therefore, the classical linear techniques for time series analysis and forecasting may not be appropriate for nonlinear processes. In recent, the BDS (Brock-Dechert-Scheinkman) statistic instead of conventional techniques has been used for detecting nonlinearity of time series. The BDS statistic was derived from the statistical properties of the correlation integral which is used to analyze chaotic system and has been effectively used for distinguishing nonlinear structure in dynamic system from random structures. DVS (Deterministic Versus Stochastic) algorithm has been used for detecting chaos and stochastic systems and for forecasting of chaotic system. This study showed the DVS algorithm can be also used for detecting nonlinearity of the time series. In this study, the stochastic and hydrologic time series are analyzed to detect their nonlinearity. The linear and nonlinear stochastic time series generated from ARMA and TAR (Threshold Auto Regressive) models, a daily streamflow at St. Johns river near Cocoa, Florida, USA and Great Salt Lake Volume (GSL) data, Utah, USA are analyzed, daily inflow series of Soyang dam and the results are compared. The results showed the BDS statistic is a powerful tool for distinguishing between linearity and nonlinearity of the time series and DVS plot can be also effectively used for distinguishing the nonlinearity of the time series.

• Journal of Korean Society of Forest Science
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• v.99 no.4
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• pp.597-602
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• 2010

The most basic matter to establish forest carbon circulation village is statistic on greenhouse gas emissions. But currently, although there is statistic on greenhouse gas emissions in the level of city or province, there is not statistic on greenhouse gas emission in village unit. According to the results, The model area is located in Seobyeok-ri, Chunyang-myeon, Bonghwa-gun, Gyeongsangbuk-do, the total $CO_2$emissions caused by energy used in the model area was $1,755tCO_2$. Heating accounts for 55% of total emissions followed by 23% for power and 22% for vehicles. The model area emitted $572tCO_2$ due to rice growing and livestock raising, accounting for approximately 24.5% of total $CO_2$ emissions. It is expected that a reduction of as much as $884tCO_2$ emissions will be made from the current $964tCO_2$ to a level of 1/12th that amount, or $80tCO_2$ by replacing heating energy currently used in the model area with wood bioenergy such as wood chips or pellets. In addition, carbon emission reduction is expected for both heating and power by replacing the power consumption in houses, buildings, and street lights with solar power.