• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.585-594
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• 2003

It has been generally recognized that conventional binomial or Poisson model provides poor fits to the actual correlated binary data due to the extra-binomial variation. A number of generalized statistical models have been proposed to account for this additional variation. Among them, beta-binomial, correlated-binomial, and modified-binomial models are binomial-related models which are frequently used in modeling the sum of n correlated binary data. In many situations, it is reasonable to assume that n correlated binary data are exchangeable, which is a special case of correlated binary data. The sum of n exchangeable correlated binary data is modeled relatively well when the above three binomial-related models are applied. But the estimation results of correlation coefficient turn to be quite different. Hence, it is important to identify which model provides better estimates of model parameters(success probability, correlation coefficient). For this purpose, a small-scale simulation study is performed to compare the behavior of above three models.

• Journal of Communications and Networks
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• 제10권4호
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• pp.444-450
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• 2008

This paper studies the performance of multiuser data networks with transmit diversity under correlated fading channels. Previous work shows that correlated fading reduces the link performance of multiple antenna systems, but how correlated fading affects the throughput of multiuser data networks is still unknown since the throughput depends not only on the link performance but also on the multiuser diversity. We derive the throughput of the multiuser data networks with various transmit diversity schemes under correlated fading channels. The impact of correlated fading on the throughput is investigated. Analytical and simulation results show that, although correlated fading is harmful for link performance, it increases the throughput of the multiuser data networks if the transmit scheme is appropriately selected.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1636-1645
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• 2016

In navigation systems that use collected trajectory for routing, the number and diversity of trajectory data are crucial despite the infeasible limitation which is that all routes should be collected in person. This paper suggests an algorithm combining trajectories only by collected GPS data and generating new routes for solving this problem. Using distance between two trajectories, the algorithm estimates road intersection, in which it also predicts the correlated direction of them with geographical coordinates and makes a decision to combine them by the correlated direction. With combined and generated trajectory data, this combination way allows trajectory-based navigation to guide more and better routes. In our study, this solution has been introduced. However, the ways in which correlated direction is decided and post-process works have been revised to use the sequential pattern of triangles' area GPS information between two trajectories makes in road intersection and intersection among sets comprised of GPS points. This, as a result, reduces unnecessary combinations resulting redundant outputs and enhances the accuracy of estimating correlated direction than before.

• 국제초고층학회논문집
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• 제10권1호
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• pp.1-8
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• 2021

Currently, big data and open data, together with traditional measured data, have come to constitute a new data environment, expanding new technical paths for quantitative analysis of the street environment. Streets provide precious linear public space in high-density residential areas. Pedestrian activities are the main body of street vitality. In this paper, 441 street segments were selected from 21 residential districts in high-density downtown area of Shanghai as cases, to quantitatively evaluate the influencing factors of pedestrian activities. Bivariate analysis was performed, and the results showed that street vitality was not only correlated with a highly populated environment, but also with other factors. In particular, the density of entrances and exits of residential properties, the proportion of walkable areas, and the density of retail and service facilities, were correlated with the vitality of street segments. The magnitudes of correlation between the street environmental factors and the pedestrian traffic differed across various trip purposes. Segment connectivity factors were more correlated with walking for leisure than for transportation. While public transportation factors were mainly correlated with walking for transportation, vehicular traffic factors were negatively correlated with walking for leisure.

• Journal of the Korean Data and Information Science Society
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• 제17권2호
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• pp.279-289
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• 2006

This paper concerns with the effects of the specialized projected for the local W university on education which was planned and conducted in October 2004. From the empirical study using the correlation analysis, regression analysis, and structured equation model, we found some results that educational service satisfaction was highly correlated with general instruction factor and hard ware factor less correlated. Also we investigated that university educational service satisfaction was deeply correlated with word of mouth.

• Journal of the Korean Data and Information Science Society
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• 제27권2호
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• pp.559-564
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• 2016

The Durbin-Watson (DW) test in regression model and the Ljung-Box (LB) test in ARMA (autoregressive moving average) model are typical examples of correlated error tests. The DW test is used for detecting autocorrelation of errors using the residuals from a regression analysis. The LB test is used for specifying the correct ARMA model using the first some sample autocorrelations based on the residuals of a tted ARMA model. In this article, simulations with four data generating processes have been carried out to evaluate their performances as correlated error tests. Our simulations show that the DW test is severely dependent on the assumed AR(1) model but isn't sensitive enough to reject the misspecified model and that the LB test reports lackluster performance in general.

• Journal of Astronomy and Space Sciences
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• 제31권4호
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• pp.325-333
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• 2014

We are motivated by both the accumulating evidence for the connection of solar variability to the chemistry of nitrogen oxide in the atmosphere and recent finding that the Galactic cosmic-ray (GCR) influx is associated with the solar north-south asymmetry. We have analyzed the measured pH in precipitation over the 109 stations distributed in the United States. We have found that data of pH in precipitation as a whole appear to be marginally anti-correlated with the solar asymmetry. That is, rain seems to become less acidic when the southern hemisphere of the Sun is more active. The acidity of rain is also found to be correlated with the atmospheric temperature, while not to be correlated with solar activity itself. We have carried on the analysis with two subsamples in which stations located in the east and in the west. We find that the pH data derived from the eastern stations which are possibly polluted by sulfur oxides and nitrogen oxides are not correlated with the solar asymmetry, but with the temperature. On the contrary, the pH data obtained from the western stations are found to be marginally anti-correlated with the solar asymmetry. In addition, the pH data obtained from the western stations are found to be correlated with the solar UV radiation. We conclude by briefly pointing out that a role of the solar asymmetry in the process of acidification of rain is to be further examined particularly when the level of pollution by sulfur oxides and nitrogen oxides is low.

• International Journal of Contents
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• 제18권1호
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• pp.17-26
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• 2022

With the acceleration of urbanization and industrialization, air pollution has become increasingly serious, and the pollution control situation is not optimistic. Climate change has become a major global challenge faced by mankind. To actively respond to climate change, China has proposed carbon peak and carbon neutral goals. However, atmospheric pollutants and meteorological factors that affect air quality are complex and changeable, and the complex relationship and correlation between them must be further clarified. This paper uses China's 2013-2018 high-resolution air pollution reanalysis open data set, as well as statistical methods of the Pearson Correlation Coefficient (PCC) to calculate and visualize the design and analysis of environmental monitoring big data, which is intuitive and it quickly demonstrated the correlation between pollutants and meteorological factors in the temporal and spatial sequence, and provided convenience for environmental management departments to use air quality routine monitoring data to enable dynamic decision-making, and promote global climate governance. The experimental results show that, apart from ozone, which is negatively correlated, the other pollutants are positively correlated; meteorological factors have a greater impact on pollutants, temperature and pollutants are negatively correlated, air pressure is positively correlated, and the correlation between humidity is insignificant. The wind speed has a significant negative correlation with the six pollutants, which has a greater impact on the diffusion of pollutants.

• Journal of Nutrition and Health
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• 제35권9호
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• pp.952-961
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• 2002

The purpose of this study was to compare nutrient intakes and the serum iron status of 74 Food and Nutrition major, and 45 non-major, female students at a university in Incheon. This cross-sectional survey was conducted using a self-administered questionnaire and the data were analyzed by the SPSS 10.0 program. The nutrient intake data collected from three-day dietary recalls were analyzed by the Computer Aided Nutritional Analysis Program. Anthropometric data and hematological indices of iron in the blood were measured. Average heights, weights, body fat and mid-upper arm circumference of Food and Nutrition major and non-major female students were 160.3 cm, 53.5kg, 25.8%, 23.7cm and 159.8cm, 55.5kg, 28.9%, 24.8cm, respectively. There were significant differences in body fat percentage and mid-upper arm circumference between the major and non-major students. In all subjects, daily dietary intakes of nutrients- except protein, vitarrlin B1, vitamin C and phosphorus - were lower than the Korean RDA. In particular, calcium and iron intakes of all subjects were under 60% of the Korean RDA. Values of RBC (red blood cell) count, Hb (hemoglobin), Hct (hematocrit), MCV (mean cell volume), MCH (mean cell hemoglobin), and MCHC (mean corpuscular hemoglobin concentration) of the non-major students were significantly higher compared to those of the major students. The diastolic blood pressure of the major students was negatively correlated with MCV, MCH, TS, and serum iron levels. Triceps skinfold thickness, mid-upper arm circumference and waist-to-hip ratios of the non-major students were negatively correlated with TIBC. Fat intake was positively correlated with RBC, Hb, Hct, and TIBC (total iron binding capacity) in the major students. Vitamin C intake was positively correlated with serum iron in the major students. Carbohydrate intake was positively correlated with Hb, Hct, and MCHC in the non-major students. Niacin and iron intakes were positively correlated with Hb and Hct in the non-major students. Therefore, nutrition education is necessary for female university students to improve nutritional status and to practice optimal nutrition strategies. (Korean J Nutrition 35(9) : 952~961, 2002)

• Communications for Statistical Applications and Methods
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• 제21권4호
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• pp.349-361
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• 2014

This paper compares of lasso type estimators in various high-dimensional data situations with sparse parameters. Lasso, adaptive lasso, fused lasso and elastic net as lasso type estimators and ridge estimator are compared via simulation in linear models with correlated and uncorrelated covariates and binary regression models with correlated covariates and discrete covariates. Each method is shown to have advantages with different penalty conditions according to sparsity patterns of regression parameters. We applied the lasso type methods to Arabidopsis microarray gene expression data to find the strongly significant genes to distinguish two groups.