Communications for Statistical Applications and Methods

  • 제10권2호
  • /
  • Pages.423-432
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  • 2003
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  • 2287-7843(pISSN)
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  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
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Spatial Data Analysis using the Kriging Method

  • 발행 : 2003.08.01
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초록

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.

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참고문헌

  1. 응용통계연구 v.9 no.1 우리나라 환경통계의 현황 박성현
  2. Proceedings of the Spring Conference 강우강도자료를 이용한 semi-variogram의 추정과 예측 유성모;엄익현
  3. Kriging기법을 이용한 강우 공간분포에 관한 연구 한국수자원공사
  4. Mathematical Geology v.21 Spatial Prediction and Ordinary Kriging Cressie,N. https://doi.org/10.1007/BF00897332
  5. Statistical for Spatial Data Cressie,N.
  6. Geostatistics Isobel Clack.;Paker,H.
  7. Geostatistics Modeling Spatial Uncertainty Jean Paul Chiles Pierre Delfiner
  8. Principles of Geostatistics v.58 Matheron,G.
  9. DACE(Design and Analysis of Computer Experiments) Sacks(et al.)
  10. Sampling Steven K. Thompson
  11. Practical Geostatistics 2000 William,V.H.;Isobel Clack

피인용 문헌

  1. 3D Modeling For Resources Estimation of Ilmenite Deposits in Jikjeon-Ri, Hadong Korea vol.26, pp.4, 2013, https://doi.org/10.9727/jmsk.2013.26.4.285
  2. The Estimation of Theoretical Semivariogram Adapting Genetic Algorithm for Kriging vol.11, pp.2, 2004, https://doi.org/10.5351/CKSS.2004.11.2.355
  3. Characteristics of PM2.5 Emission and Distribution in a Highly Commercialized Area in Seoul, Korea vol.31, pp.2, 2015, https://doi.org/10.5572/KOSAE.2015.31.2.097