• Proceedings of the Korean Society of Plant Pathology Conference
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• 2003.10a
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• pp.87.3-88
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• 2003

TiO$_2$photocatalytic ozonation was attempted to disinfect fungal pathogens causing postharvest spoilage of kiwifruits and to decompose fungicide residuals on kiwifruits. TiO$_2$Photocatalytic ozonation process synergistically degraded organic compound and inhibited conidial germination of the fungal pathogen compared to single treatment of ozonation or photocatalysis. The efficient control of fungal spoilage and degradation of residual fungicide on kiwifruits indicate that TiO$_2$photocatalytic ozonation is a very attractive method for postharvest disease control of kiwifruits as an alternative to fungicides application.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.155-167
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• 2007

Knowing the time of the process change could lead to quicker identification of the responsible special cause and less process down time, and it could help to reduce the probability of incorrectly identifying the special cause. In this paper, we propose the maximum likelihood estimator (MLE) for the process change point when a control chart is used in monitoring the mean of a process in which the observations can be modeled as an AR(1) process plus an additional random error. The performance of the proposed MLE is compared to the performance of the built-in estimator when they are used in EWMA charts based on the residuals. The results show that the proposed MLE provides good performance in terms of both accuracy and precision of the estimator.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.241-251
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• 1997

Several studies have bee down on the work of dynamic graphical methods for regression diagnostics. The main propose of the methods were to investigate (1) the effects of change of data, or (2) the effects of change of regression coefficients on the regression models. But, by contrast, we can also investigate the effects of change of regression residuals on the regression model. This method can be used in fitting better a certain set of observations to a regression model than the other observations. Our research team approaches regression diagnostics by using dynamic graphics (REDS), and we introduce REDS in this thesis.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.179-183
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• 2010

In this paper, we consider the change point problem in diusion processes based on discretely observed sample. Particularly, we consider the change point test for the dispersion parameter when the drift has unknown parameters. In performing a test, we employ the cusum of squares test based on the residuals. It is shown that the test has a limiting distribution of the sup of a Brownian bridge. A simulation result as to the Ornstein-Uhlenbeck process is provided for illustration. It demonstrates the validity of our test.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.453-458
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• 2009

In this paper, we consider Jarque-Bera (JB) normality test for the innovations of ARMA-GARCH models. In financial applications, JB test based on the residuals are routinely used for the normality of ARMA-GARCH innovations without a justification. However, the validity of JB test should be justified in advance of the actual practice (Lee et al., 2009). Through the simulation study, it is found that the validity of JB test depends on the shape of test statistic. Specifically, when the constant term is involved in ARMA model, a certain type of residual based JB test produces severe size distortions.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.665-682
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• 2005

The sample reuse bootstrap technique has been successful to attract both applied and theoretical statisticians since its origination. In recent years a good deal of attention has been focused on the applications of bootstrap methods in regression analysis. It is easier but more accurate computation methods heavily depend on high-speed computers and warrant tough mathematical justification for their validity. It is now evident that the presence of multiple unusual observations could make a great deal of damage to the inferential procedure. We suspect that bootstrap methods may not be free from this problem. We at first present few examples in favour of our suspicion and propose a new method diagnostic-before-bootstrap method for regression purpose. The usefulness of our newly proposed method is investigated through few well-known examples and a Monte Carlo simulation under a variety of error and leverage structures.

• Health Policy and Management
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• v.13 no.3
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• pp.91-103
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• 2003

The purpose of this study was to provide basic reference data for stabilization scheme of health expenditure through forecasting of health expenditure. The authors analyzed the health expenditure from 1985 to 2000 that had been calculated by Korean institute for health and social affair using transfer function model as ARIMA model with input series. They used GDP as the input series for more precise forecasting. The model of error term was identified ARIMA(2,2,0) and Portmanteau statics of residuals was not significant. Forecasting health expenditure as percent of GDP at 2010 was 6.8%, under assumption of 5% GDP increase rate. Moreover that was 7.4%, under assumption of 3% GDP increase rate and that was 6.4%, under assumption of 7% GDP increase rate.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.5 no.1
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• pp.66-72
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• 1987

It is well known that a triangulateration net is superior to a trilateration net or triangulation net in a same configuration. In general, to explain this nature is not easy because the large residuals and reference variance are revealed in the adjustment of a heterogeneous network. In this paper the precision and the reliability of network are discussed, and the considerations of simultaneous adjustment are covered A practical example shows that the concept and criteria of reliability give better estimate than the precision in heterogeneous network.

• Journal of Korean Society for Quality Management
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• v.28 no.1
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• pp.1-12
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• 2000

Since Black Monday there has been a rash of systems developments which aimed at automating and upgrading the surveillance mechanism of monitoring the many facets of security trading. A more sophisticated mathematical model for detecting abnormal trading activities was created by Davis and Ord of Penn State along with Nobel prize laureates Solow and Modigliani of MIT. They used CAPM(Capital Asset Pricing Model) to explain the movements of stock price and applied an idea of residuals to detect unusual movements. In this paper, their idea is discussed and a new method is proposed, which involves a confidence interval of future observation in linear regression. One of the examples of the stock watch system adopting this statistical method is also presented.

• Journal of Korean Society for Quality Management
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• v.20 no.1
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• pp.1-10
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• 1992

When we compare different control charting schemes, the average run length of each control chart is usually used. The use of the average run length implies that there is unbounded number of samples or observations. The regression recursive residuals, however, have been applied to the cumulative sum chart to detect whether the mean or variance changes. To implement choice of decision interval, we calculate the probability that certain fixed number of control statistics stay in the in-control state. This probability can be used as the significance level of a test for detecting the change in the residual mean or variance of the data with a finite number of observations.