Fitting Rainfall Data by Using Cubic Spline Interpolation
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This study discusses the application of two cubic spline i.e. natural and not-a-knot end boundary conditions to visualize and predict the rainfall data. The interpolation and the analysis of the rainfall data will be done on a monthly basis by using the MATLAB software. The rainfall data is obtained from Malaysia Meteorology Department for Ipoh and Petaling Jaya in year 2014 and 2015. The interpolating curves are then being compared and if there is any negative value on the interpolating curve on some sub-interval, that part will be replaced by using the Piecewise Cubic Hermite Interpolating Polynomial (PCHIP). We discuss the missing data imputation by using both splines.
2002 ◽
Vol 19
(5)
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pp. 345-363
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1994 ◽
Vol 11
(4)
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pp. 425-450
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An Improved Novel Index Measured Segmentation Based Imputation Algorithm for Missing Data Imputation
2017 ◽
Vol 7
(6)
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pp. 283-286
2011 ◽
Vol 25
(4)
◽
pp. 343-347
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Keyword(s):
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