• Title/Summary/Keyword: 포아송 회귀분석

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Spatial analysis on forest fire occurrence with meteorological data (기상인자를 이용한 산불 발생 공간 분석)

  • Kwak, Han-Bin;Lee, Woo-Kyun;Lee, Si-Young;Won, Myung-Soo;Koo, Kyo-Sang;Lee, Myung-Bo
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2009.04a
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    • pp.279-281
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    • 2009
  • 우리나라 산불은 대부분 인간에 의해서 발생한다고 알려져 있다. 하지만 그것이 반드시 기상요인을 받지 않는다고는 볼 수 없다. 연중 대부분의 산불이 봄철 건조한 시기에 일어나기 때문이다. 본 연구는 이처럼 산불 발생과 관련이 있는 기상인자 중 기온과 강수량, 습도를 중심으로 산불 발생과의 관련성을 알아보고자 하였다. 몇몇 독립변수들을 통제하기 위해 지형 지리 인자들이 분석에 포함되었다. 시간을 두고 발생하는 이산형 사건 분석에 적합한 포아송 회귀분석을 실시하기 위해 산불 발생 지점의 점 자료를 래스터화하여 사용하였다.

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Analysis of Violent Crime Count Data Based on Bivariate Conditional Auto-Regressive Model (이변량 조건부자기회귀모형을이용한강력범죄자료분석)

  • Choi, Jung-Soon;Park, Man-Sik;Won, Yu-Bok;Kim, Hag-Yeol;Heo, Tae-Young
    • 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.

Analysis of the relationship between regulation compliance and occupational injuries - Focusing on logistic and poisson regression analysis - (규제 순응도와 산업재해 발생 수준간의 관계 분석 - 로지스틱 회귀분석과 포아송 회귀분석을 중심으로 -)

  • Rhee, Kyung-Yong;Kim, Ki-Sik;Yoon, Young-Shik
    • Journal of the Korea Safety Management & Science
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    • v.15 no.2
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    • pp.9-20
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    • 2013
  • OSHA(Occupational Safety and Health Act) generally regulates employer's business principles in the workplace to maintain safety environment. This act has the fundamental purpose to protect employee's safety and health in the workplace by reducing industrial accidents. Authors tried to investigate the correlation between 'occupational injuries and illnesses' and level of regulation compliance using Survey on Current Status of Occupational Safety & Health data by the various statistical methods, such as generalized regression analysis, logistic regression analysis and poison regression analysis in order to compare the results of those methods. The results have shown that the significant affecting compliance factors were different among those statistical methods. This means that specific interpretation should be considered based on each statistical method. In the future, relevant statistical technique will be developed considering the distribution type of occupational injuries.

A Reliability Prediction Method for Weapon Systems using Support Vector Regression (지지벡터회귀분석을 이용한 무기체계 신뢰도 예측기법)

  • Na, Il-Yong
    • Journal of the Korea Institute of Military Science and Technology
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    • v.16 no.5
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    • pp.675-682
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    • 2013
  • Reliability analysis and prediction of next failure time is critical to sustain weapon systems, concerning scheduled maintenance, spare parts replacement and maintenance interventions, etc. Since 1981, many methodology derived from various probabilistic and statistical theories has been suggested to do that activity. Nowadays, many A.I. tools have been used to support these predictions. Support Vector Regression(SVR) is a nonlinear regression technique extended from support vector machine. SVR can fit data flexibly and it has a wide variety of applications. This paper utilizes SVM and SVR with combining time series to predict the next failure time based on historical failure data. A numerical case using failure data from the military equipment is presented to demonstrate the performance of the proposed approach. Finally, the proposed approach is proved meaningful to predict next failure point and to estimate instantaneous failure rate and MTBF.

확률회귀모형을 이용한 고속도로의 사고요인 분석

  • Lee, Gi-Yeong;Lee, Yong-Taek
    • 도로교통
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    • s.94
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    • pp.51-64
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    • 2003
  • 본 연구는 사고요인과 사고모형의 문헌고찰을 통해 고속도로를 주행하는 버스와 화물차의 사고모형을 개발하고 그 적용방안에 대해 고찰하고자 수행되었다. 고속도로 사고 중 대형차로 인한 차량당 사고율은 승용차보다 월등히 높아 사고의 심각성을 나타내고 있으며, 따라서 이에 대한 별도의 검토가 필요한 시점에 와 있다. 특히 본 연구에 활용된 자료는 비집계된 사상자수로 구간자료를 집합화함으로써 발생하는 문제점을 해소할 수 있다. 모형의 분석기법으로 국내의 경우, 대부분 단순회귀식으로 사고모형을 개발, 적용하여 왔으나 사고수와 사상자수의 특성상 이산적 확률변수로 해석하여 포아송분포와 음이항분포로 적용하는 것이 바람직하다. 따라서 본 연구에서는 버스와 화물차의 사고유형별로 적합한 사고 모형을 개발하여 이로 인한 인사사고 요인에 대한 영향을 분석하고 그 적용방안을 제시하였다. 이러한 연구는 도로설계, 운영, 교통법규, 교통행정 등의 분야에서 거시적인 정책적 방향성을 제시하리라 판단된다. 특히 본 연구는 고속도로 운영주체인 한국도로공사의 고속도로사고조서를 바탕으로 사고유형별 사고모형을 개발, 적용한 것으로 고속도로의 안정성 향상을 위한 제반 정책 수립에 기초자료로 활용될 것으로 기대된다.

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Accident Models of Circular Intersections by Type in Korea (사고유형에 따른 원형교차로 사고모형)

  • Han, Su-San;Kim, Kyung-Hwan;Park, Byung-Ho
    • International Journal of Highway Engineering
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    • v.13 no.3
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    • pp.103-110
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    • 2011
  • This study deals with the traffic accidents by type. The objectives are to analyze the characteristics of 2 accident types, and to develop the models by type. In pursuing the above, this paper gives particular attentions to testing the differences between by type two groups, and developing the models (Poisson and negative binomial regressions) using the data of domestic circular intersections. The main results are as follows. First, the number of accidents in vehicle vehicle was analyzed to account for about 73.41% of total and to be higher than vehicle people. Second, two Poisson models and two negative binomial models which were all statistically significant were developed using vehicle people accidents and vehicle vehicle accidents as dependant variables. Finally, the traffic volume as common variable was selected in the models, and right-turn slip lane, speed hump, the number of driveways, the number of pedestrian crossings as specific variables of the models were selected.

Comparative Analysis of Medical Use of Spine Specialty Hospitals and Nonspecialty Hospitals (척추전문병원과 비전문병원의 의료이용 비교분석)

  • Young-Noh Lee;Yun-Ji Jeong;Kwang-Soo Lee
    • Health Policy and Management
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    • v.34 no.1
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    • pp.26-37
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    • 2024
  • Background: The purpose of this study was to compare and analyze the differences in charges and length of stay per case between spine specialty hospitals and non-specialty hospitals, and to identify the factors that influenced them. Methods: This study used claims data from the Health Insurance Review and Assessment Service, including inpatient visits from January 2021 to December 2022. The healthcare facility status data was used to identify the characteristics of study hospitals. Multilevel analysis was conducted to identify factors associated with the charges and Poisson regression analysis was conducted to analyze the length of stay between spine specialty hospitals and non-specialty hospitals. There were 32,015 cases of spine specialty hospitals and 17,555 cases of non-specialty hospitals. Results: For four of five common spinal surgeries, specialty hospitals shaped longer length of stay than those of non-specialty hospitals. Multilevel and Poisson regression analysis revealed that regardless of the type of surgery, higher age and higher Charlson comorbidity index scores were significantly associated with an increase in both the charges per case and length of stay (p<0.05). However, when hospitals were located in metropolitan areas, there was a significant decrease (p<0.05). Conclusion: This study found that specialty hospital had higher inpatient charges and loner length of stay contrary to the previous study results. Further studies will be needed to find which contribute to the differences.

A new sample selection model for overdispersed count data (과대산포 가산자료의 새로운 표본선택모형)

  • Jo, Sung Eun;Zhao, Jun;Kim, Hyoung-Moon
    • The Korean Journal of Applied Statistics
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    • v.31 no.6
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    • pp.733-749
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    • 2018
  • Sample selection arises as a result of the partial observability of the outcome of interest in a study. Heckman introduced a sample selection model to analyze such data and proposed a full maximum likelihood estimation method under the assumption of normality. Recently sample selection models for binomial and Poisson response variables have been proposed. Based on the theory of symmetry-modulated distribution, we extend these to a model for overdispersed count data. This type of data with no sample selection is often modeled using negative binomial distribution. Hence we propose a sample selection model for overdispersed count data using the negative binomial distribution. A real data application is employed. Simulation studies reveal that our estimation method based on profile log-likelihood is stable.

IoT Utilization for Predicting the Risk of Circulatory System Diseases and Medical Expenses Due to Short-term Carbon Monoxide Exposure (일산화탄소 단기 노출에 따른 순환계통 질환 위험과 진료비용 예측을 위한 IoT 활용 방안)

  • Lee, Sangho;Cho, Kwangmoon
    • Journal of Internet of Things and Convergence
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    • v.6 no.4
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    • pp.7-14
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    • 2020
  • This study analyzed the effect of the number of deaths of circulatory system diseases according to 12-day short-term exposure of carbon monoxide from January 2010 to December 2018, and predicted the future treatment cost of circulatory system diseases according to increased carbon monoxide concentration. Data were extracted from Air Korea of Korea Environment Corporation and Korea Statistical Office, and analyzed using Poisson regression analysis and ARIMA intervention model. For statistical processing, SPSS Ver. 21.0 program was used. The results of the study are as follows. First, as a result of analyzing the relationship between the impact of short-term carbon monoxide exposure on death of circulatory system diseases from the day to the previous 11 days, it was found that the previous 11 days had the highest impact. Second, with the increase in carbon monoxide concentration, the future circulatory system disease treatment cost was estimated at 10,123 billion won in 2019, higher than the observed value of 9,443 billion won at the end of December 2018. In addition, when summarized by month, it can be seen that the cost of treatment for circulatory diseases increases from January to December, reflecting seasonal fluctuations. Through such research, the future for a healthy life for all citizens can be realized by distributing various devices and equipment utilizing IoT to preemptively respond to the increase in air pollutants such as carbon monoxide.

Analyzing the Characteristics of Traffic Accidents and Developing the Models by Day and Night in the Case of the Cheongju Arterial Link Sections (청주시 간선가로 구간의 주.야간 사고특성 및 모형개발)

  • Kim, Tae-Young;Lim, Jin-Kang;Park, Byung-Ho
    • International Journal of Highway Engineering
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    • v.13 no.1
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    • pp.13-19
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    • 2011
  • The purpose of this study is to analyze the characteristics of traffic accidents and to develop the models by day and night-time in the case of the arterial link sections. In pursuing the above, this study uses the 224 accident data occurred at the 24 arterial link sections in Cheongju. The main results analyzed are as follows. First, it was analyzed that the number of accidents during day was more than night, but the accidents rate during night was higher than day. Second, four models which were all statistically significant were developed. Finally, the differences between the day and night models were comparatively analyzed using independent variables.