• Title/Summary/Keyword: spatial statistics

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A Study on the Characteristics of the Spatial Distribution of Sex Crimes: Spatial Analysis based on Environmental Criminology (성폭력 범죄의 공간적 분포 특성에 관한 연구: 환경범죄학에 기반한 공간 분석)

  • Lee, Gunhak;Jin, Chanwoo;Kim, Jiwoo;Kim, Wanhee
    • Journal of the Korean Geographical Society
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    • v.51 no.6
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    • pp.853-871
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    • 2016
  • The interest in the prevention of sex crimes and social secure is growing as the number of cases by sexual offences becomes higher. Although various punishable ways have been introduced so far, increasing sex crime is still going on. Thus, effectiveness of legal systems for preventing crimes is questionable. More recently, the approach for environmental criminology has been paid attention for reducing criminal opportunities through environmental design and management of crimes. This study attempts to look over the spatial distribution of sexual crimes in the context of environmental criminology, and examine the correlation between regional environmental factors and the occurrence of sexual crimes empirically. To do this, we visualized the map for sex crimes at the macro-scale and explored the spatial distribution of sexual crimes and spatial clusters based on various spatial statistics using sex crime data published online by the ministry of gender equality and family. Also, we derived the environmental characteristics of sexual crimes by multivariate regression analysis on a large number of explanatory variables of regional environment. Our results will help to understand the current situation and spatial aspects of sex crimes in the nation more realistically. Further, it is respected that our results might be useful basic information for establishing regional policies and plans for the prevention of the sexual crime and enhanced public policing.

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Forward/Backward First Order Statistics Algorithm for the estimation of DOA in a Multipath environment (다중경로 환경에서 DOA를 추정하기 위한 Forward/Backward First Order Statistics Algorithm)

  • 김한수
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1998.06c
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    • pp.221-224
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    • 1998
  • 간섭신호가 원하는 신호에 coherent한 경우에는 원하는 신호와 간섭신호간의 cross correlation에 의해 공분산 행렬의 rank가 줄어들게 되어 coherent한 간섭신호의 도래각을 추정할 수 없게 된다. 이러한 문제를 해결하기 위해 발표된 기존의 방법중 대칭 어레이(Symmetric array)방법은 계산량이 많아지고 공간 스무딩(Spatial Smoothing)방법은 array aperture size에서 손해를 보게 되어 분해능이 떨어지는 단점이 있다[1,2,3].

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MOMENTS OF VARIOGRAM ESTIMATOR FOR A GENERALIZED SKEW t DISTRIBUTION

  • KIM HYOUNG-MOON
    • Journal of the Korean Statistical Society
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    • v.34 no.2
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    • pp.109-123
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    • 2005
  • Variogram estimation is an important step of spatial statistics since it determines the kriging weights. Matheron's variogram estimator can be written as a quadratic form of the observed data. In this paper, we extend a skew t distribution to a generalized skew t distribution and moments of the variogram estimator for a generalized skew t distribution are derived in closed forms. After calculating the correlation structure of the variogram estimator, variogram fitting by generalized least squares is discussed.

Distributed Processing Method of Hotspot Spatial Analysis Based on Hadoop and Spark (하둡 및 Spark 기반 공간 통계 핫스팟 분석의 분산처리 방안 연구)

  • Kim, Changsoo;Lee, Joosub;Hwang, KyuMoon;Sung, Hyojin
    • Journal of KIISE
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    • v.45 no.2
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    • pp.99-105
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    • 2018
  • One of the spatial statistical analysis, hotspot analysis is one of easy method of see spatial patterns. It is based on the concept that "Adjacent ones are more relevant than those that are far away". However, in hotspot analysis is spatial adjacency must be considered, Therefore, distributed processing is not easy. In this paper, we proposed a distributed algorithm design for hotspot spatial analysis. Its performance was compared to standalone system and Hadoop, Spark based processing. As a result, it is compare to standalone system, Performance improvement rate of Hadoop at 625.89% and Spark at 870.14%. Furthermore, performance improvement rate is high at Spark processing than Hadoop at as more large data set.

A Space Model to Annual Rainfall in South Korea

  • Lee, Eui-Kyoo
    • Communications for Statistical Applications and Methods
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    • v.10 no.2
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    • pp.445-456
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    • 2003
  • Spatial data are usually obtained at selected locations even though they are potentially available at all locations in a continuous region. Moreover the monitoring locations are clustered in some regions, sparse in other regions. One important goal of spatial data analysis is to predict unknown response values at any location throughout a region of interest. Thus, an appropriate space model should be set up and their estimates and predictions must be accompanied by measures of uncertainty. In this study we see that a space model proposed allows a best interpolation to annual rainfall data in South Korea.

Spatial Data Analysis using the Kriging Method

  • Jang, Jihui;Hong, Taekyong;NamKung, Pyong
    • Communications for Statistical Applications and Methods
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    • v.10 no.2
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    • pp.423-432
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    • 2003
  • The data observed at different positions are called the estimate of interested variable at new observation point on the Kriging utilize the space estimate technique, in which case there is correlation spatially. In this paper we provide the estimate for Variogram and Kriging methods as a field of kriging theory and dealt with actually measured data. And at the same time we forecast the amount of ozone that was not measured at this point by Kriging method and compared Ordinary Kriging method with Inverse Distance Kriging method.

County Level Clustering on Alcohol and HIV Mortality

  • Park, Byeonghwa
    • Communications for Statistical Applications and Methods
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    • v.20 no.1
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    • pp.53-62
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    • 2013
  • This study focuses on spatial/temporal relationship deaths caused by Human Immunodeficiency Virus (HIV) and Alcohol Use Disorder (AUD). Several studies have found links between these two diseases. By looking for clusters in mortality of Alcohol and HIV related deaths this study contributes to the field through the identification of exact spatial/temporal time of high and low occurrence risks based on the observed over the expected number of deaths. This study does not provide political or social interpretations of the data. It merely wants to show where clusters are found.

Visualization and interpretation of cancer data using linked micromap plots

  • Park, Se Jin;Ahn, Jeong Yong
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.6
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    • pp.1531-1538
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    • 2014
  • The causes of cancer are diverse, complex, and only partially understood. Many factors including health behaviors, socioeconomic environments and geographical locations can directly damage genes or combine with existing genetic faults within cells to cause cancerous mutations. Collecting the cancer data and reporting the statistics, therefore, are important to help identify health trends and establish normal health changes in geographical areas. In this article, we analyzed cancer data and demon-strated how spatial patterns of the age-standardized rate and health indicators can be examined visually and simultaneously using linked micromap plots. As a result of data analysis, the age-standardized rate has positive correlativity with thyroid and breast cancer, but the rate has negative correlativity with smoking and drinking. In addition, the regions with high age-standardized rate are located in southwest and the areas of high population density while the standardized mortality ratio is higher in southwest and northeast where there are lots of rural areas.

Bayesian Spatial Modeling of Precipitation Data

  • Heo, Tae-Young;Park, Man-Sik
    • The Korean Journal of Applied Statistics
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    • v.22 no.2
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    • pp.425-433
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    • 2009
  • Spatial models suitable for describing the evolving random fields in climate and environmental systems have been developed by many researchers. In general, rainfall in South Korea is highly variable in intensity and amount across space. This study characterizes the monthly and regional variation of rainfall fields using the spatial modeling. The main objective of this research is spatial prediction with the Bayesian hierarchical modeling (kriging) in order to further our understanding of water resources over space. We use the Bayesian approach in order to estimate the parameters and produce more reliable prediction. The Bayesian kriging also provides a promising solution for analyzing and predicting rainfall data.

Evaluation of Spatial Consolidation Settlement by Probabilistic Method (확률론적 방법을 이용한 공간적 압밀침하량 평가)

  • Kim, Dong-Hee;Choi, Young-Min;Ko, Seong-Kwon;Lee, Woo-Jin
    • Proceedings of the Korean Geotechical Society Conference
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    • 2010.03a
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    • pp.475-479
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    • 2010
  • For a rational evaluation of the spatial distribution of consolidation settlement, it is necessary to adopt probabilistic method. In this study, mean and standard deviation of consolidation settlement of whole analysis region are evaluated by using the spatial distribution of consolidation layer which is estimated from kriging and statistics of soil properties. Using these results and probabilistic method, the area need to be raised the ground level for balancing the final design ground level are determined.

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