• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.227-237
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• 2014

We use the regression model with the indicator variables in the case that we use qualitative variables as some predictor variables in regression analysis. We use the ANCOVA(Analysis of Covariance) model when comparing the response variable among groups while statistically controlling for variation in the response variable caused by a variation in the covariate. DD-plot can be used as a graphical exploratory data analysis tool before the confirmatory data analysis. With the DD-plot, we can discriminate the difference of groups in the regression model with the indicator variables or the ANCOVA model at a glance. Making DD-plot does not demand the statistical model assumption about error terms in regression model. Several examples show the usefulness of DD-plots as a graphical exploratory data analysis tool for the regression analysis.

• Journal of the Korean Statistical Society
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• v.27 no.1
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• pp.67-90
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• 1998

In this paper we analytically study model misspecification that arises in regression analysis of nonstationary seasonal time series. We assume the underlying data generating process is a seasonally or a regularly and seasonally integrated process. We first study consequences of totally misspecified cases where seasonal indicator variables, a linear time trend, or another statistically independent seasonally integrated process are used as predictor variables in order to model the nonstationary seasonal behavior of the dependent variable. Then we study consequences of partially misspecified cases where the dependent variable and a predictor variable are cointegrated at some, but not all of the frequencies corresponding to the nonstationary roots.

• The KIPS Transactions:PartC
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• v.11C no.3
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• pp.353-360
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• 2004

In this Paper, We propose an efficient iteration decoding control method with variable iteration decoding of iteration codes decoding using Cyclic Redundancy Check. As the number of iterations increases, the bit error rate and frame error rate of the decoder decrease and the incremental improvement gradually diminishes. However, when the iteration decoding number is increased, it require much delay and amount of processing time for decoding. Also, It can be observed the error nor that the performance cannot be improved even though increasing of the number of iterations and SNR. So, Suitable number of iterations for stopping criterion is required. we propose variable iteration control method to adapt variation of channel using Frame Error-Check indicator. Therefore, the amount of computation and the number of iterations required for iteration decoding with CRC method can be reduced without sacrificing performance.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.6
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• pp.71-84
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• 2017

Over the past decade, we have witnessed Serious Debates in MISQ and Other Journals Between Two Camps that have Differing Views on the use of Causal Indicators to Measure Constructs. There is the Camp that advocates Causal Indicators (ADVOCATE) and the Camp that opposes Their Usage (OPPONENT). The Debates have been primarily centered on the OPPONENT's Argument that the Meaning of a Latent Variable is determined by its Outcome Variables. However, Little Effort has been made to Validate the ADVOCATE's Dispute (Against the OPPONENT's Arguments) that the Meaning of a Latent Variable is decided by its Causal Indicators if there is no Misspecification. Our Study precisely examines the Integrity of the Argument. For this, we empirically examine how the two Primary Psychometric Properties-Comprehensiveness and Interrelationship-of Causal Indicators Influence Theory Testing between Latent Variables through Three Different Tests (i.e., Comprehensive Test, Interrelationship Test, and Mixed Test). Conducted on Two Different Datasets, Our Analysis Consistently Reveals that Structural Path Coefficients are Hardly Sensitive to the Changes (i.e., Misspecification) in the Properties of Causal Indicators. The Discovery offers Important Evidence that the Sound Theoretical Logic of a Causal Model is not in Sync with the Empirical Mechanism of Parameter Estimation. This Underscores that a Latent Variable Formed by Causal Indicators is empirically an elusive notion that is Difficult to Operationalize. As Our Results have Significant Implications on the Integrity of Numerous IS studies which have conducted Theory or Hypothesis Testing Using Causal Indicators, we strongly advocate Open Discussions among Methodologists regarding Our Findings and Their Implications for Both Published IS Research and Future Practices.

• Journal of Korean Academy of Nursing
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• v.21 no.2
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• pp.195-203
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• 1991

Correlations among body weight and sociodemographic factors, including life - style were tested as social determinants of health in a sample of 5,201 adults in Korea. The aim of this study was to determine the extent to which sociodemographic variables and life-style associated health behaviors explain body weight distribution. A second aim was to explain the relation of body weight and health status to stress the importance of body weight as an early risk indicator of health status. The canonical correlation between the weight distribution(underweight and overweight) and the independent variables was 0.29, 17% of the total variance was explained. Perceived health level represented the highest contribution(canonical coefficient 0.82) to body weight. Sociodemographic factors such as sex, economic status, and life-style factors such as smoking, exercise, regular meais and sleep showed comparatively high contributions to body weight. The relevance of body weight for health status including the rate of chronic disease and the rate of medical utilization was significant. Especially, underweight was clarified as being mere important than overweight to morbidity level and medical utilization. These findings suggest that perceived body weight is an important indicator of health status and is thus a valuable variable to be considered for nursing intervention and health education related to the promotion of health.

• Journal of The Korean Digital Architecture Interior Association
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• v.10 no.2
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• pp.13-20
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• 2010

Uncertainty in housing price fluctuation has great impact on the overall economy due to importance of housing market as both place of residence and investment target. Therefore, estimating housing market condition is a highly important task in terms of setting national policy. Primary indicator of the housing market is a ratio between rent and transaction price of housing. The research explores dynamic relationships between Rent-Transaction price ratio, housing transaction price and jeonse rental price, using Vector Autoregressive Model, in order to demonstrate significance of shifting rent-transaction price that is subject to changes in housing transaction and housing rental market. The research applied housing transaction price index and housing rental price index as an indicator to measure transaction and rental price of housing. The price index and data for price ratio was derived from statistical data of the Kookmin Bank. The time-series data contains monthly data ranging between January 1999 and November 2009; the data was log transformed to convert to level variable. The analysis result suggests that the rising ratio between rent-transaction price of housing should be interpreted as a precursor for rise of housing transaction price, rather than judging as a mere indicator of a current trend.

• Structural Engineering and Mechanics
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• v.4 no.2
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• pp.191-202
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• 1996

This paper presents a construction of adaptive boundary element for the problem with mixed boundary conditions such as heat transfer between heated body surface and surrounding medium. The scheme is based on the sample point error analysis and on the extended error indicator, proposed earlier by the authors for the potential and elastostatic problems, and extended successfully to multidomain and thermoelastic analyses. Since the field variable is connected with its derivative on the boundary, their errors are also interconnected by the specified condition. The extended error indicator on each boundary element is modified to meet with the situation. Two numerical examples are shown to indicate the differences due to the prescribed boundary conditions.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.3 no.3
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• pp.143-150
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• 1999

Mobile source emissions are important inputs to photochemical air quality models. Since most mobile source emissions are calculated at the county-level, these emission should be geographically allocated to the computational grid cells of a photochemical air quality model prior to running the model. The traditional method for the spatial allocation of these emissions has been to use a "spatial surrogate indicator" such as population, since grid-specific emission calculations are very labor-intensive and expensive, plus the necessary data are often not available for such grid resolutions. Accordingly, new spatial surrogate indicators for mobile source emissions(specifically for highway emissions) were developed using Geographic Information Systems(GIS) tools due to the spatially variable nature of mobile source emissions. These newly developed spatial surrogate indicators appear to be more appropriate for the allocation of highway emissions than the population surrogate indicator. It was also revealed that the conventional spatial allocation method underestimates the maximum levels of air pollutant emmissions.mmissions.

• Journal of Power Electronics
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• v.11 no.4
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• pp.424-429
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• 2011

In this paper, the simulator of an on-line monitoring system for the range extender electric vehicle has been developed. The messages from the four control modules, the air pressure and fuel level sensors data, and the on/off switching states of 31 indicator lamps can be received through the control area network (CAN), and displayed on the graphic panel. The simulator was designed using the four DSP boards, variable resistors, and toggle switches instead of the four control modules, sensors, and switching state of indicator lamps on an actual series hybrid electric vehicle (SHEV) bus, respectively. The performance of the monitoring technologies was verified with the simulator at the laboratory, and then it was tested on an actual SHEV bus. The simulator is very useful at the initial development of the monitoring system at the hybrid-type or electrical vehicles.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.31-39
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• 2021

This study empirically examines the proposition that the domestic fundamentals of a nation can emerge as absorptive capacity factors to reap the benefits of inward FDI. The study is contextualized in Asia, set from1982 to 2017, and data is grouped into low-income and lower-middle-income economies, in comparison to high-income and upper-middle-income economies, catering to different geographical regions within Asia. The investigation is based on a series of absorptive capacity factors such as infrastructure, human capital, domestic credit, and health indicator. The methodological analysis is premised on dynamic panel structure and employs the Generalized Method of Moments (GMM) estimation technique. The empirical findings suggest that that the infrastructure variable appears to be the major absorptive capacity factor for both groups of countries. The health indicator, on the other hand, can help reap the benefits of inward FDI, but only if the threshold level is met. The selected economies must achieve this threshold level to reap the benefits of FDI. To absorb the benefits of inward FDI, countries must be proactive in providing sound infrastructure and implementing proper healthcare measures.