• Journal of Korean Society for Quality Management
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• v.34 no.3
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• pp.66-72
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• 2006

The process capability indices are widely used to measure the capability of the process to manufacture items within the specified tolerance. Most evaluations on process capability indices focus on point estimates, which may result in unreliable assessments of process performance. The index $C_p$ has been widely used in various industries to assess process performance. In this paper, we propose new testing procedure on assessing $C_p$ index for practitioners to use in determining whether a given process is capable. The provided approach is easy to use and the decision making is more reliable. Whether a process is clearly normal or nonnormal, our bootstrap testing procedure could be applied effectively without the complexity of calculation. A numerical result based on the proposed approach is illustrated.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.185-188
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• 2008

This paper introduces the Bootstrap method for statistical analysis of noise and vibration spectrum in aeronautic and space fields. Generally, all components of a launch vehicle and its payloads are subjected to high intensive noise and vibration environment during the lift-off phase and the ascent phase through Mach =1 and Max Q. In order to verify their survivabilities against these severe vibroacoustic environments during qualification tests and acceptance tests, it is most important to estimate the proper upper limits of the environmental condition. Although NASA has typically utilized the Normal Tolerance Limit method in deriving these levels, the reference[1] says that the Bootstrap can be also an alternative method to estimate the maximum expected environments. In this paper, a general procedure of the Bootstrap method is summarized, and it is applied to analyze acceleration power spectral density functions, which were measured during acoustic test on the upper stage of KSLV-I.

• Communications for Statistical Applications and Methods
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• v.16 no.4
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• pp.697-705
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• 2009

The Pearson chi-squared statistic or the deviance statistic is widely used in assessing the goodness-of-fit of the generalized linear models. But these statistics are not proper in the situation of continuous explanatory variables which results in the sparseness of cell frequencies. We propose a goodness-of-fit test statistic for the cumulative logit models with ordinal responses. We consider the grouping of a dataset based on the ordinal scores obtained by fitting the assumed model. We propose the Pearson chi-squared type test statistic, which is obtained from the cross-classified table formed by the subgroups of ordinal scores and the response categories. Because the limiting distribution of the chi-squared type statistic is intractable we suggest the parametric bootstrap testing procedure to approximate the distribution of the proposed test statistic.

• The Korean Journal of Applied Statistics
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• v.32 no.5
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• pp.753-761
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• 2019

A test procedure based on a Kendall's τ statistic is proposed for the association of bivariate interval censored data. In particular, a leverage bootstrap technique is applied to replace unknown failure times and a classical adjustment method is applied for treating tied observations. The suggested method shows desirable results in simulation studies. An AIDS dataset is analyzed with the suggested method.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1057-1065
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• 2010

In this paper we discuss some cautionary notes in using the Pearson chi-squared test statistic for the goodness-of-fit of the ordinal response model. If a model includes continuous type explanatory variables, the resulting table from the t of a model is not a regular one in the sense that the cell boundaries are not fixed but randomly determined by some other criteria. The chi-squared statistic from this kind of table does not have a limiting chi-square distribution in general and we need to be very cautious of the use of a chi-squared type goodness-of-t test. We also study the limiting distribution of the chi-squared type statistic for testing the goodness-of-t of cumulative logit models with ordinal responses. The regularity conditions necessary to the limiting distribution will be reformulated in the framework of the cumulative logit model by modifying those of Moore and Spruill (1975). Due to the complex limiting distribution, a parametric bootstrap testing procedure is a good alternative and we explained the suggested method through a practical example of an ordinal response dataset.

• The Korean Journal of Financial Management
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• v.24 no.2
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• pp.183-206
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• 2007

The price-dividend ratio is one of the most frequently used financial variables to predict long-horizon stock return. However, the persistency of the price-dividend ratio is found to cause the spuriousness of the stock return prediction regression. The stable relationship between the stock price and the dividend, however, seems to weaken after World War II and to experience structural break. In this paper, we identify a structural change in the cointegrating relationship between the log of the stock price and the log of the dividend. Confirming a structural break in 1962, we subdivide the sample and apply the fully modified estimator to correct for the nonstationarity of the regressor. With the subdivided sample, we exercise the nonparametric bootstrap procedure to derive the empirical distribution of the test statistics and fail to find return predictability in each subsample period.

• Advances in concrete construction
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• v.1 no.1
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• pp.85-102
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• 2013

Prior concrete strength distributions can be updated by using direct information from test results as well as by taking into account indirect information due to conformity control. Due to the filtering effect of conformity control, the distribution of the material property in the accepted inspected lots will have lower fraction defectives in comparison to the distribution of the entire production (before or without inspection). A methodology is presented to quantify this influence in a Bayesian framework based on prior knowledge with respect to the hyperparameters of concrete strength distributions. An algorithm is presented in order to update prior distributions through numerical integration, taking into account the operating characteristic of the applied conformity criteria, calculated based on Monte Carlo simulations. Different examples are given to derive suitable hyperparameters for incoming strength distributions of concrete offered for conformity assessment, using updated available prior information, maximum-likelihood estimators or a bootstrap procedure. Furthermore, the updating procedure based on direct as well as indirect information obtained by conformity assessment is illustrated and used to quantify the filtering effect of conformity criteria on concrete strength distributions in case of a specific set of conformity criteria.

• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.459-471
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• 2010

Higher quality level is generally perceived by customers as improved performance by assigning a correspondingly higher satisfaction score. Usually, the quality level is measured by process capability indices. The index is used to determine whether a production process is capable of producing items within a specified tolerance. The third generation index $C_{pmk}$ is more powerful than two useful indices $C_p$ and $C_{pk}$. which have been widely used in six sigma industries to assess process performance. Most evaluations on process capability indices focus on point estimates, which may result in unreliable assessments of process performance. In this paper, we consider better testing procedure on assessing process capability index $C_{pmk}$ for practitioners to use in determining whether a given process is capable. It is easy to use the proposed method for assessing process capability index $C_{pmk}$. Whether a process is clearly normal or nonnormal, our bootstrap testing procedure could be applied effectively without the complexity of calculation. A numerical result based on our proposed method is illustrated.

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.451-464
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• 2008

Six sigma is the rating that signifies "best in clas", with only 3.4 defects per million units or operations. Higher sigma quality level is generally perceived by customers as improved performance by assigning a correspondingly higher satisfaction score. The process capability indices and the sigma level $Z_{st}$ have been widely used in six sigma industries to assess process performance. Most evaluations on process capability indices focus on point estimates, which may result in unreliable assessments of process performance. In this paper, we consider statistical inference for process capability indices $C_p$, $C_{pk}$ and $C_{pm}$. Also, we study better testing procedure on assessing sigma level $Z_{st}$ and capability index $C_{pm}$, for practitioners to use in determining whether a given process is capable. The proposed method is easy to use and the decision making is more reliable. Whether a process is clearly normal or nonnormal, our bootstrap testing procedure could be applied effectively without the complexity of calculation. A numerical result based on our proposed method is illustrated.

• Journal of Information Technology Applications and Management
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• v.18 no.4
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• pp.21-40
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• 2011

Emoticons perform an important role as an enhancement to written communication, in areas such as Windows Live Messenger instant messaging, e-mails, mobile Short Message Services (SMS), and others. Emoticons are graphic images used in communications to indicate the feelings of people exchanging messages via mobile technology. In this research, the perceived usefulness of the emoticon in mobile phone text messages is verified with consumers using the five construct model of Huang. A K-means clustering technique for separating three groups based on levels of perceived usefulness of mobile emoticons is used with a structural equation model test using Smart PLS 2.0, and the bootstrap re-sampling procedure. We analyzed relationships among use of emoticons, enjoyment, interaction, information richness, and perceived usefulness. The results show there are relationships among use of emoticons, enjoyment, interaction, perceived usefulness, and information richness, however enjoyment of emoticons did not significantly affect the perceived usefulness of messages with emoticons alone. The results suggest emoticons have different affects on emotion in both mobile, and Messenger contexts. Our study did not consider more detailed media properties, and thus more studies are needed. Our research results contribute to mobile communication activation, provides companies with an understanding of key characteristics of consumers who use emoticons, and provides useful implications for improving management and marketing strategies.