ESTIMASI: Journal of Statistics and Its Application
Vol. 4, No. 2, Juli, 2023 : Estimasi

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

Fitri Annisa (a:1:{s:5:"en_US"
s:15:"colloge student"
})

Raupong Raupong (Unknown)
Sitti Sahriman (Unknown)



Article Info

Publish Date
04 Aug 2023

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.

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Journal Info

Abbrev

ESTIMASI

Publisher

Subject

Mathematics

Description

ESTIMASI: Journal of Statistics and Its Application, is a journal published by the Department of Statistics, Faculty of Mathematics and Natural Sciences, Hasanuddin University. ESTIMASI is a peer – reviewed journal with the online submission system for the dissemination of statistics and its ...