Performa Model Statistical Downscaling dengan Peubah Dummy Berdasarkan K-Means dan Average Linkage

Authors

  • Fitri Annisa a:1:{s:5:"en_US";s:15:"colloge student";}
  • Raupong Raupong
  • Sitti Sahriman

Keywords:

Average Linkage, Estimastion Liu Regression, Global Circulation Model, K-Means, Dummy Variabel, Principal Component Regression, Statistical Downscaling

Abstract

Climate change that occurs is often used to predict future climate conditions. For future climate predictions it is only possible to use climate models. One of the climate models used to predict climate conditions is the Global Circulation Models (GCM). GCM represents global climatic conditions but not on a regional or local scale. The approach that has been widely used to bridge the difference in scale is statistical downscaling. Large-scale GCM data allows for multicollinearity. estimation liu regression and principal component regression is used to solve the multicollinearity problem. In addition, dummy variables based on k-means and average linkage are used in the model to overcome the heterogeneous variance of residue. There are 4 dummy variables in the cluster technique. In this paper, Liu k-means regression model parameter estimation method is the best model.

References

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Published

2023-08-04