Journal of the Korean Data Analysis Society

Korean Data Analysis Society (한국자료분석학회)
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A Study on Shipments of Swimming Crab Using Negative Binomial Regression Model

음이항회귀모형을 이용한 꽃게 출하량에 관한 연구

  • Nam, Yeongeun (Division of Mathematics and Big Data Science, Daegu University) ;
  • Seo, Jihyun (Division of Mathematics and Big Data Science, Daegu University) ;
  • Choi, Gayeong (Division of Mathematics and Big Data Science, Daegu University) ;
  • Lee, Kyeongjun (Division of Mathematics and Big Data Science, Daegu University)
  • 남영은 (대구대학교 수리빅데이터학부 통계빅데이터전공) ;
  • 서지현 (대구대학교 수리빅데이터학부 통계빅데이터전공) ;
  • 최가영 (대구대학교 수리빅데이터학부 통계빅데이터전공) ;
  • 이경준 (대구대학교 수리빅데이터학부 통계빅데이터전공)
  • Received : 2018.11.20
  • Accepted : 2018.12.20
  • Published : 2018.12.31

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Abstract

The purpose of this paper is to analyse the effect of ocean weather factors on shipments of swimming crab. We use the data of data portal and ocean weather factors (mean wind velocity, mean atmospheric pressure, mean relative humidity, mean air temperature, mean water temperature, mean maximum wave height, mean significant wave height, maximum significant wave height, maximum wave height, mean wave period, maximum wave period). We did statistical analysis using Poisson regression analysis and negative binomial regression analysis. As the result of study, important factors influential in the shipments of swimming crab turn out to be mean wind velocity, mean atmospheric pressure, mean relative humidity, mean water temperature, maximum wave height, mean wave period and maximum wave period. the shipments of swimming crab increases as mean wind velocity, mean atmospheric pressure, mean relative humidity, mean water temperature increases or mean wave period increase. However, as maximum wave height, maximum wave period decreases, the shipment of swimming crab increases.

본 연구는 해양기상관측자료인 평균 풍속, 평균 기압, 평균 상대습도, 평균 기온, 평균 수온, 평균 최대파고, 평균 유의파고, 최고 유의파고, 최고 최대파고, 평균 파주기, 최고 파주기 등의 요인들이 꽃게의 출하건수에 미치는 영향을 음이항 회귀모형을 통해 확인하고 모형적합을 시도하였다. 염분과 수온이 갑각류의 성숙 및 산란에 영향을 미치며, 특히 수온은 성장에 관여하는 대사 작용에 영향을 끼친다고 알려져 있고 최근 지구온난화로 인해, 얼음이 녹으면서 바다의 유의, 최대, 평균파고와 파주기, 그리고 수온까지 영향을 미치고 있어 꽃게 출하건수를 예측하는데 있어 중요한 변수라고 생각할 수 있다. 분석결과 꽃게의 출하건수에 영향을 주는 요인은 평균 풍속, 평균 기압, 평균 상대습도, 평균 해수온도, 최대 파고, 평균 파주기, 최대 파주기로 결정되었다. 꽃게의 출하건수는 평균 풍속, 평균 기압, 평균 상대습도, 평균 해수온도, 평균 파주기가 높을수록 증가하는 경향을 보이고 있고, 최대 파고, 최대 파주기가 낮을수록 꽃게의 출하건수는 증가하는 경향을 보이고 있었다.

Keywords

Acknowledgement

Supported by : 대구대학교

References

  1. An, Y., Choi, S., Choi, S., Yoon, H. (2012). A characteristics of biological resources of portunus trituberculatus (Miers, 1876) around the Chilsan inland Younggwang, Korea, Journal of the Korean Society of Marin Environment & Safety, 18, 115-122. (in Korean). https://doi.org/10.7837/kosomes.2012.18.2.115
  2. Cameron, A. C., Trivedi, P. K. (1986). Economic models based on count data: Comparisons and applications of some estimators, Journal of Applied Econometrics, 1, 29-53. https://doi.org/10.1002/jae.3950010104
  3. Cha, H., Kim, J. (2013). Cross correlation analysis of gamma exposure rates and rainfall, hours of saylight, average wind speed in Gangneung area, Journal of the Korean Society of Radiology, 32, 347-352. (in Korean).
  4. Cho, E. Y., An, H. (2018). Analysis of the relationship between regional prevalence and the average concentration of particulate matter using beta regression, Journal of the Korean Data Analysis Society, 20, 1791-1800. (in Korean).
  5. Cho, J., Shin, C. H., Yoon, S. B. (2013). Numerical study on sea state parameters affecting rip current at Haeundae beach: Wave period, height, direction and tidal elevation, Journal of the Korea Water Resources Association, 46, 205-218. (in Korean). https://doi.org/10.3741/JKWRA.2013.46.2.205
  6. Chun, H., Ahn, C. (2012). A study on organizational outcome of life insurance solicitors using negative binomial regression model, Journal of Insurance and Finance, 23, 29-60. (in Korean).
  7. Cox, D. R. (1983). Some remarks on overdispersion, Biometrika, 70, 497-505.
  8. Gurmu, S. (1991). Tests for detecting overdispersion in the positive Poisson regression model, Journal of Business and Economic Statistics, 9, 215-222.
  9. Kang, S. (2015). The impact of the supply regulation on the price in farming olive flounder, Environmental and Resource Economics Review, 24, 709-725. (in Korean). https://doi.org/10.15266/KEREA.2015.24.4.709
  10. Kang, B., Heo, T. Y. (2017). Comparison of planar and network spatial point pattern analysis for traffic accidents: Focused on Gangnam-gu in Seoul, Journal of the Koran Data Analysis Society, 19, 2433-2445. (in Korean).
  11. Kim, K. B., Hong, S. Y. (2004). Effects of temperature on larval growth and survival in the wrinkled swimming crab (Liocarcinus corrugatus) (Brachyura: Portunidae) reared in the laboratory, Korean Journal of Fisheries and Aquatic Sciences, 37, 186-191. (in Korean). https://doi.org/10.5657/kfas.2004.37.3.186
  12. Kim, H., Seo, Y., Cha, H., Kang, H., Zhang, C. (2018). A study on the estimation of potential yield for Korean west coast fisheries using the holistic production method (HPM), Journal of the Korean Society of Fisheries and Ocean Technology, 54, 38-53. (in Korean). https://doi.org/10.3796/KSFOT.2018.54.1.038
  13. Lee, J., Lim, S., Cho, S., Choi, S., Heo, H., Lee, S. (2009). Effect of relative humidity and storage temperature on the quality of green tea powder, Journal of the Korean Society of Food Science and Nutrition, 38, 83-88. (in Korean). https://doi.org/10.3746/jkfn.2009.38.1.083
  14. Lee, H., Yang, J. (2015). An optimal management model with regard to the swimming crabs in Yellow sea Yeonpyongdo in Korea: Simulation and implications, Journal of International Area Studies, 19, 415-433. (in Korean).
  15. Lim, D., Lho, S. (2018). The economic impacts of weather on the textile and apparel industry and implications, Journal of the Korean Data Analysis Society, 20, 1359-1367. (in Korean).
  16. Min, H., Kim, C. (2006). Inter-annual variability and long-term trend of coastal sea surface temperature in Korea, Ocean and Polar Research, 28, 415-423. (in Korean). https://doi.org/10.4217/OPR.2006.28.4.415
  17. Na, J., Han, S., Seo, J., Noh, Y., Kang, I. (1997). Empirical orthogonal function analysis of surface pressure, sea surface temperature and winds over the East sea of the Korea, Korean Journal of Fisheries and Aquatic Sciences, 30, 188-202. (in Korean).
  18. Park, N., Jang, D. (2008). Mapping of temperature and rainfall using DEM and multi-variate kriging, Journal of the Korean Geographical Society, 43, 1002-1015. (in Korean).
  19. Park, H. C., Park, H. W. (2017). Disaster communication networks on Twitter: Gyeongju earthquake, Journal of the Korean Data Analysis Society, 19, 291-302. (in Korean).