• Proceedings of the Safety Management and Science Conference
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• 2007.04a
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• pp.335-346
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• 2007

This paper introduces reliability stress screening(RSS) for electronic hardware and components. This study also shows reliability centered maintenance(RCM), and reliability growth models. Moreover, this paper presents goodness-of-fit tests and estimation methods of power law model.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.41-61
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• 2001

The minimum negative exponential disparity estimator(MNEDE), introduced by Lindsay(1994), is an excellenet competitor to the minimum Hellinger distance estimator(Beran 1977) as a robust and yet efficient alternative to the maximum likelihood estimator in parametric models. In this paper we define the negative exponential deviance test(NEDT) as an analog of the likelihood ratio test(LRT), and show that the NEDT is asymptotically equivalent to he LRT at the model and under a sequence of contiguous alternatives. We establish that the asymptotic strong breakdown point for a class of minimum disparity estimators, containing the MNEDE, is at least 1/2 in continuous models. This result leads us to anticipate robustness of the NEDT under data contamination, and we demonstrate it empirically. In fact, in the simulation settings considered here the empirical level of the NEDT show more stability than the Hellinger deviance test(Simpson 1989). The NEDT is illustrated through an example data set. We also define a goodness-of-fit statistic to assess adequacy of a specified parametric model, and establish its asymptotic normality under the null hypothesis.

• Communications for Statistical Applications and Methods
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• v.26 no.5
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• pp.431-443
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• 2019

Goodness-of-fit techniques are an important topic in statistical analysis. Censored data occur frequently in survival experiments; therefore, many studies are conducted when data are censored. In this paper we mainly consider test statistics based on the empirical distribution function (EDF) to test normal distributions with unknown location and scale parameters when data are randomly censored. The most famous EDF test statistic is the Kolmogorov-Smirnov; in addition, the quadratic statistics such as the $Cram{\acute{e}}r-von$ Mises and the Anderson-Darling statistic are well known. The $Cram{\acute{e}}r-von$ Mises statistic is generalized to randomly censored cases by Koziol and Green (Biometrika, 63, 465-474, 1976). In this paper, we generalize the Anderson-Darling statistic to randomly censored data using the Kaplan-Meier estimator as it was done by Koziol and Green. A simulation study is conducted under a particular censorship model proposed by Koziol and Green. Through a simulation study, the generalized Anderson-Darling statistic shows the best power against almost all alternatives considered among the three EDF statistics we take into account.

• Proceedings of the Safety Management and Science Conference
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• 2007.04a
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• pp.295-307
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• 2007

This paper introduces statistical test principles, statistical procedures and tests for exponential distribution. This paper also shows compliance test plans for success ratio and constant failure rate, and goodness-of-fit tests for Weibull distribution. Moreover, this paper presents procedures for comparision of two constant failure rates, and dependability of products containing reused parts.

• Proceedings of the KAIS Fall Conference
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• 2012.05a
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• pp.22-24
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• 2012

The tools that classify the severity of patients based on the prediction of mortality include APACHE, SAPS, and MPM. Theses tools rely crucially on the evaluation of patients' general clinical status on the first date of their admission to ICU. Nursing activities are one of the most crucial factors influencing on the quality of treatment that patients receive and one of the contributing factors for their prognosis and safety. The purpose of this study was to identify the goodness-of-fit of CPSCS of critical patient severity classification system(CPSCS) and Glasgow coma scale(GCS) and the clinical usefulness of its death rate prediction. Data were collected from the medical records of 187 neurological patients who were admitted to the ICU of C University Hospital. The data were analyzed through $x^2$ test, t-test, Mann-Whitney, Kruskal-Wallis, goodness-of-fit test, and ROC curve. In accordance with patients' general and clinical characteristics, patient mortality turned out to be statistically different depending on ICU stay, endotracheal intubation, central venous catheter, and severity by CPSCS. Homer-Lemeshow goodness-of-fit tests were CPSCS and GCS and the results of the discrimination test using the ROC curve were $CPSCS_0$, .734, $GCS_0$,.583, $CPSCS_{24}$,.734, $GCS_{24}$, .612, $CPSCS_{48}$,.591, $GCS_{48}$,.646, $CPSCS_{72}$,.622, and $GCS_{72}$,.623. Logistic regression analysis showed that each point on the CPSCS score signifies1.034 higher likelihood of dying. Applied to neurologically ill patients, early CPSCS scores can be regarded as a useful tool.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2012.04a
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• pp.190-193
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• 2012

The tools that classify the severity of patients based on the prediction of mortality include APACHE, SAPS, and MPM. Theses tools rely crucially on the evaluation of patients' general clinical status on the first date of their admission to ICU. Nursing activities are one of the most crucial factors influencing on the quality of treatment that patients receive and one of the contributing factors for their prognosis and safety. The purpose of this study was to identify the goodness-of-fit of CPSCS of critical patient severity classification system(CPSCS) and Glasgow coma scale(GCS) and the clinical usefulness of its death rate prediction. Data were collected from the medical records of 187 neurological patients who were admitted to the ICU of C University Hospital. The data were analyzed through $x^2$ test, t-test, Mann-Whitney, Kruskal-Wallis, goodness-of-fit test, and ROC curve. In accordance with patients' general and clinical characteristics, patient mortality turned out to be statistically different depending on ICU stay, endotracheal intubation, central venous catheter, and severity by CPSCS. Homer-Lemeshow goodness-of-fit tests were CPSCS and GCS and the results of the discrimination test using the ROC curve were $CPSCS_0$,.734, $GCS_0$,.583, $CPSCS_{24}$,.734, $GCS_{24}$,.612, $CPSCS_{48}$,.591, $GCS_{48}$,.646, $CPSCS_{72}$,.622, and $GCS_{72}$,.623. Logistic regression analysis showed that each point on the CPSCS score signifies1.034 higher likelihood of dying. Applied to neurologically ill patients, early CPSCS scores can be regarded as a useful tool.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.119-129
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• 2022

In this paper, we predict the earthquake magnitudes which were recently occurred in Gyeongju and Pohang, using statistical methods based on historical data. For this purpose, we use the five-year block maximum data of 1392~1771 period, which has a relatively high annual density, among the historical earthquake magnitude data of the Chosun Dynasty. Then, we present the prediction and analysis of earthquake magnitudes for the return level over return period in the Chosun Dynasty using the extreme value theory based on the distribution of generalized extreme values (GEV). We use maximum likelihood estimation (MLE) and L-moments estimation for parameters of GEV distribution. In particular, this study also demonstrates via the goodness-of-fit tests that the GEV distribution can be an appropriate analytical model for these historical earthquake magnitude data.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2813-2827
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• 2018

Progressive censoring schemes have become quite popular in reliability study. Under progressive censored data, however, some units can be failed between two points of observation with exact times of failure of these units unobserved. For example, loss may arise in life-testing experiments when the failure times of some units were not observed due to mechanical or experimental difficulties. Therefore, multiply progressive censoring scheme was introduced. So, we derives a maximum likelihood estimator of the parameter of exponential distribution. And we introduced the goodness-of-fit test statistics using order statistic and Lorenz curve. We carried out Monte Carlo simulation to compare the proposed test statistics. In addition, real data set have been analysed. In Weibull and chi-squared distributions, the test statistics using Lorenz curve are more powerful than test statistics using order statistics.

• The Korean Journal of Applied Statistics
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• v.2 no.2
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• pp.79-89
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• 1989

Modified Pearson $X^2$ statistic is concerned. Moreover the four statistics(Pearson, Wald, modified sample design effects and reduction factor) are compared in one-stage sampling situation. In case of categorical of fit and independence tests for sample data above, it is shown that there is a significant behavior between Pearson $X^2$ and Wald statistic, but minor difference in modified statistics by simulation methods.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.27-36
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• 2005

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates Per fault. This Paper Proposes reliability model using the generalized gamma distribution, which can capture the monotonic increasing(or monotonic decreasing) nature of the failure occurrence rate per fault. Equations to estimate the parameters of the generalized gamma finite failure NHPP model based on failure data collected in the form of interfailure times are developed. For the sake of proposing shape parameter of the generalized gamma distribution, used to the special pattern. Data set, where the underlying failure process could not be adequately described by the knowing models, which motivated the development of the gamma or Weibull model. Analysis of failure data set for the generalized gamma modell, using arithmetic and Laplace trend tests . goodness-of-fit test, bias tests is presented.