• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.231-239
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• 2015

A Poisson model is the first choice for counts data. Quasi Poisson or negative binomial models are usually used in cases of over (or under) dispersed data. However, these models might be unsuitable if the data consist of excessive number of zeros (zero inflated data). For zero inflated counts data, Zero Inflated Poisson (ZIP) or Zero Inflated Negative Binomial (ZINB) models are recommended to address the issue. In this paper, we further considered a situation where zero inflated data are spatially correlated. A mixed effect model with random effects that account for spatial autocorrelation is used to fit the data.

• Journal of Korea Water Resources Association
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• v.37 no.10
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• pp.813-822
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• 2004

This study quantifies and compares the drought return and duration characteristics by applying the Poisson process as well as based on by analyzing the observed data directly. The drought spatial distributions derived for the Gyunggi province are also compared. The monthly rainfall data are used to construct the SPI as a drought index. Especially, this study focuses on the evaluation of the Poisson process model when applying it to various data lengths such as in the spatial analysis 'of drought. Summarizing the results are as follows. (1) The Poisson process is found to be effective for the quantification of drought, especially when the data length is short. When applying the Poisson process, two neighboring sites are found insensitive to the data length to show similar drought characteristics, so the overall drought pattern becomes smoother than that derived directly from the observed data. (2) When the data length is very different site by site, the spatial analysis of drought based on a model application seems better than that based on the direct data analysis. This study also found more obvious spatial pattern of drought occurrence and duration when applying the Poisson process.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.421-430
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• 2006

In sample survey sample designs are performed by geographically-based domain such as countries, states and metropolitan areas. However mostly statistics of interests are smaller domain than sample designed domain. Then sample sizes are typically small or even zero within the domain of interest. Shin and Lee(2003) mentioned Spatial Autoregressive(SAR) model in small area estimation model-based method and show the effectiveness by MSE. In this study, Bayesian Auto-Poisson Model is applied in model-based small area estimation method and compare the results with SAR model using MSE ME and bias check diagnosis using regression line. In this paper Survey of Disability, Aging and Cares(SDAC) data are used for simulation studies.

• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.413-421
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• 2010

In this study, we considered bivariate conditional auto-regressive model taking into account spatial association as well as correlation between the two dependent variables, which are the counts of murder and burglary. We conducted likelihood ratio test for checking over-dispersion issues prior to applying spatial poisson models. For the real application, we used the annual counts of violent crimes at 25 districts of Seoul in 2007. The statistical results are visually illustrated by geographical information system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.2
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• pp.333-340
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• 2016

The aim of this study is to specifically understand the characteristics of the crime by empirical analysis for the determining factors that affect determining the crime through the space syntax in Busan. In this study, poisson regression and negative binomial regression were used for accurate analysis. 8 variables that were significant of the total 13 variables. The summary if this study based on the results is as follow. Statistically significant variables are female ratio, over 65 population ratio, administration are and commercial area ratio in characteristics. And the more CCTVs a region has, the lower crime rate it shows. As a results of examing whether space syntax variables can predict crime occurrence places. Space with low connectivity come to be a crime causal factor because they have few other related spaces and thereby have low possibility of sudden appearance of interrupters, which results in low surveillance levels of foot passengers. It will provide the basic data that can contribute to urban planning and implementation of crime prevention aspects.

• Spatial Information Research
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• v.11 no.3
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• pp.227-240
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• 2003

The primary focus of this study is to provide a general methodology which can be utilized to understand and analyze environmental issues such as long term ecosystem dynamics and land use/cover change by development of 2D dynamic landscape models and model-based simulation. Change processes in land cover and ecosystem function can be understood in terms of the spatial and temporal distribution of land cover resources. In development of a system to understand major processes of change and obtain predictive information, first of all, spatial heterogeneity is to be taken into account because landscape spatial pattern affects on land cover change and interaction between different land cover types. Therefore, the relationship between pattern and processes is to be included in the research. Landscape modeling requires different approach depending on the definition, assumption, and rules employed for mechanism behind the processes such as spatial event process, land degradation, deforestration, desertification, and change in an urban environment. The rule-based models are described in the paper for land cover change by natural fires. Finally, a case study is presented as an example using spatial modeling and simulation to study and synthesize patterns and processes at different scales ranging from fine-scale to global scale.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.213-223
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• 2021

It is very important to build a safe walking environment for children because children are more likely to be exposed to traffic accidents than adults due to their behavioral and physical characteristics. Therefore, this study analyzed the characteristics of road and transportation safety facilities that affect pedestrian traffic accidents around school zones using spatial poisson regression. The pedestrian-vehicle crash data in Seoul 2016-2018 was provided by the Traffic Accident Analysis System(TAAS). The main analysis results are as follow; First, the more intersections and the higher percentage of neighborhood roads in the school zone, the higher the risk of pedestrian traffic accidents. Second, the pedestrian push button was found to reduce the occurrence of pedestrian traffic accidents. Third, except for the pedestrian push button, none of the transportation safety facilities considered in this study were effective in reducing the risk of pedestrian traffic accidents. On the other hand, if not only the improvement of physical facilities but also non-physical factors such traffic safety education are supported, the effect for reducing traffic pedestrian traffic accidents in the school zone is expected to be further maximized.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.335-344
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• 2010

Reliability of the estimation is usually damaged in the situation where a linear regression model without spatial dependencies is employed to the spatial data analysis. In this study, we considered the conditional autoregressive model in order to construct spatial association structures and estimate the parameters via the Bayesian approaches. Finally, we compared the performances of the models with spatial effects and the ones without spatial effects. We analyzed the yearly total crime count data measured from each of 25 districts in Seoul, South Korea in 2007.

• Journal of Korean Society of Transportation
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• v.34 no.6
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• pp.489-498
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• 2016

The objective of this study is to develop road traffic accident model involving child pedestrian especially at school zones and its surrounding area. The analysis is based upon traffic accident data collected near sixty elementary schools in City of Cheongju during 2012 and 2014. This study results in two statistical models ; one is to predict the number of road traffic accidents involving children, and the other is to predict EPDO(Equivalent Prperty Damage Only). These models are represented as Poisson models. which are statistically significant with the likelihood ratios of 0.533 and 0.273. The common explanatory variables of these models are the ratio of road section with more than 4 lanes, the number of entrance and exit, the number of signalized crosswalk in school zone, the number of school zone signage including road surface marking, and the number of speed limit signs. The specific variables are the length of road stretch in school zone, the number of reflector mirrors, and the number of signalized crosswalk outside school zone. It is concluded that these types of road safety facilities can reduce the number of traffic accidents involving children at school zones and its surrounding area.

• Journal of Korea Water Resources Association
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• v.47 no.10
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• pp.959-972
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• 2014

In this study, a space-time rainfall grid field generation model based on multifractal theory was verified using nine flood events in the upstream watershed of Chungju dam in South Korea. For this purpose, KMA radar rainfall data sets were analyzed for the space-time multifractal characteristics. Simulated rainfall fields that represent the multifractal characteristics of observed rainfall field were reproduced using the space-time rainfall grid field generation model with log-Poisson distribution and three-dimension wavelet function. Simulated rainfall fields were applied to the S-RAT model as input data and compared with both observed rainfall fields and low-resolution rainfall field runoff. Error analyses using RMSE, RRMSE, MAE, SS, NPE and PTE indicated that the peak discharge increases about 20.03% and the time to peak decreases about 0.81%.