• The Korean Journal of Applied Statistics
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• v.35 no.6
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• pp.703-724
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• 2022

Although longitudinal studies mainly produce multivariate longitudinal data, most of existing statistical models analyze univariate longitudinal data and there is a limitation to explain complex correlations properly. Therefore, this paper describes various methods of modeling the covariance matrix to explain the complex correlations. Among them, modified Cholesky decomposition, modified Cholesky block decomposition, and hypersphere decomposition are reviewed. In this paper, we review these methods and analyze Korean children and youth panel (KCYP) data are analyzed using the Bayesian method. The KCYP data are multivariate longitudinal data that have response variables: School adaptation, academic achievement, and dependence on mobile phones. Assuming that the correlation structure and the innovation standard deviation structure are different, several models are compared. For the most suitable model, all explanatory variables are significant for school adaptation, and academic achievement and only household income appears as insignificant variables when cell phone dependence is a response variable.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.18-18
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• 1996

This paper reviews some of the most prominent and promising areas of chemical process control both in relations to batch and continuous processes. These areas include the modeling, optimization, control and monitoring of chemical processes and entire plants. Most of these areas explicitly utilize a model of the process. For this purpose the types of models used are examined in some detail. These types of models are categorized in knowledge-driven and datadriven classes. In the areas of modeling and optimization, attention is paid to batch reactors using the Tendency Modeling approach. These Tendency models consist of data- and knowledge-driven components and are often called Gray or Hybrid models. In the case of continuous processes, emphasis is placed in the closed-loop identification of a state space model and their use in Model Predictive Control nonlinear processes, such as the Fluidized Catalytic Cracking process. The effective monitoring of multivariate process is examined through the use of statistical charts obtained by the use of Principal Component Analysis (PMC). Static and dynamic charts account for the cross and auto-correlation of the substantial number of variables measured on-line. Centralized and de-centralized chart also aim in isolating the source of process disturbances so that they can be eliminated. Even though significant progress has been made during the last decade, the challenges for the next ten years are substantial. Present progress is strongly influenced by the economical benefits industry is deriving from the use of these advanced techniques. Future progress will be further catalyzed from the harmonious collaboration of University and Industrial researchers.

• Journal of Digital Convergence
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• v.4 no.2
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• pp.41-49
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• 2006

This study tried to find the determine of intention to mobile game service acceptance. Our research proposes the theoretical model consisting of factors such as perceived usefulness, perceived ease of using the mobile phone, perceived price. The data was analyzed using LISREL based on th structural equation modeling, a second-generation multivariate technique. The result shows that the perceived usefulness have significant effects on the mobile game service acceptance.

• 한국디지털정책학회:학술대회논문집
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• 2006.06a
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• pp.399-407
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• 2006

This study tried to fine the determine of intention to mobile game service acceptance. Our research proposes the theoretical model consisting of factors such as perceived usefulness, perceived ease of using the mobiliphone, perceived price. The data were analyzed using LISREL based on th structural equation modeling, a second-generation multivariate technique. The result show that the perceived usefulness have significant effects on the mobile game service acceptance.

• Nuclear Engineering and Technology
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• v.37 no.2
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• pp.177-184
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• 2005

The Multivariate State Estimation Technique (MSET) is being used in Nuclear Power Plants for sensor and equipment condition monitoring. This paper presents the use of regularization methods for optimizing MSET's predictive performance. The techniques are applied to a simulated data set and a data set obtained from a nuclear power plant currently implementing empirical, on-line, equipment condition monitoring techniques. The results show that regularization greatly enhances the predictive performance. Additionally, the selection of prototype vectors is investigated and a local modeling method is presented that can be applied when computational speed is desired.

• Communications for Statistical Applications and Methods
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• v.3 no.2
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• pp.249-273
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• 1996

This paper reviews and develops several statistical models for extreme values, based on threshold methodology. Extreme values of a time series are modeled in terms of tails which are defined as truncated forms of original variables, and Markov property is imposed on the tails. Tails of the generalized extreme value distribution and a multivariate extreme value distributively, of the tails of the series. These models are then applied to real ozone data series collected in the Chicago area. A major concern is given to detecting any possible trend in the extreme values.

• Journal of Korea Water Resources Association
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• v.51 no.1
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• pp.49-60
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• 2018

The multivariate regional frequency analysis has many advantages such as an adaption of regional parameters and consideration of a correlated structure of the data. The multivariate regional frequency analysis can provide the broader and more detailed information for the hydrological variables. The multivariate regional frequency analysis has not been attempted to model hydrological variables in South Korea yet. Therefore, it is required to investigate the applicability of the multivariate regional frequency analysis in the modeling of the hydrological variables. The current study investigated the applicability of the homogeneous region delineation and their characteristics in bivariate regional frequency analysis of annual maximum rainfall depth-duration data. The K-medoid method was employed as a clustering method. The discordancy and heterogeneous measures were used to assess the appropriateness of the delineation results. According to the results of the clustering analysis, the employed stations could be grouped into five regions. All stations at three of the five regions led to acceptable values of discordancy measures than the threshold. The stations where have short record length led to the large discordancy measures. All grouped regions were identified as a homogeneous region based on heterogeneous measure estimates. It was observed that there are strong cross-correlations among the stations in the same region.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.209-222
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• 2015

Time series are used in many studies for model building and analysis. We must be very careful to understand the kind of time series data used in the analysis. In this review article, we will begin with some issues related to the use of aggregate and systematic sampling time series. Since several time series are often used in a study of the relationship of variables, we will also consider vector time series modeling and analysis. Although the basic procedures of model building between univariate time series and vector time series are the same, there are some important phenomena which are unique to vector time series. Therefore, we will also discuss some issues related to vector time models. Understanding these issues is important when we use time series data in modeling and analysis, regardless of whether it is a univariate or multivariate time series.

• Journal of Elementary Mathematics Education in Korea
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• v.24 no.1
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• pp.31-52
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• 2020

This study aimed to examine the relationships among elementary mathematics teachers' self-efficacy beliefs, constructivist beliefs, and years of experience. This study used the primary data set of 299 Korean elementary school teachers. Exploratory and confirmatory factor analysis, Pearson's correlation test, multivariate analysis of variance, and structural equation modeling were conducted. This study found that mathematics teachers' self-efficacy beliefs were positively related to their years of experience and constructivist beliefs, whereas there was no significant association between teachers' years of experience and constructivist beliefs. Additionally, teachers' self-efficacy beliefs significantly mediated the relationship between years of experience and constructivist beliefs.

• Clinics in Shoulder and Elbow
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• v.26 no.1
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• pp.41-48
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• 2023

Background: Shoulder instability procedures have low morbidity; however, complications can arise that result in readmission to an inpatient healthcare facility. The purpose of this study is to identify the demographics and risk factors associated with unplanned 30-day readmission and reoperation following arthroscopic and open treatment for shoulder instability. Methods: The American College of Surgeons National Surgical Quality Improvement Program database was queried to find patients who underwent shoulder instability surgery from 2015 to 2019. Independent sample Student t-tests, chi-square, and (where appropriate) Fisher's exact tests were used in univariate analyses to identify demographic, lifestyle, and perioperative variables related to 30-day readmission and reoperation following repair for shoulder instability. Multivariate logistic regression modeling was subsequently performed. Results: Of the 11,230 cases included in our sample, only 0.54% were readmitted, and 0.23% underwent reoperation within the 30-day postoperative period. Multivariate logistic regression modeling confirmed that the following patient variables were associated with statistically significantly increased odds of readmission and reoperation: open repair, congestive heart failure (CHF), and hospital length of stay. Conclusions: Unplanned 30-day readmission and reoperation after shoulder instability surgery is infrequent. Patients with American Society of Anesthesiologists class II, CHF, longer than average hospital length of stay, or an open procedure have higher odds of readmission than patients without those factors. Patients who have CHF, longer than average hospital length of stay, and open surgery have higher odds of reoperation than others. Arthroscopic procedures should be used to manage shoulder instability, if possible. Level of evidence: III.