A Plot The Functional Rainfall Data B Plot The Smoothed Functional

A Plot The Functional Rainfall Data B Plot The Smoothed Functional A descriptive statistic of the functional data depicted the mean and variation of the rainfall curve over time, while the functional principal component analysis measured the temporal. The major step after getting data is to convert the discrete data into functional data, the next step is to smooth the functional data and the last two steps are to obtain the functional results of rainfall data as shown in fig. 1.

A Plot The Functional Rainfall Data B Plot The Smoothed Functional The r software was used to process the data obtained from the tropical rainfall measuring mission in taiz city. the functional rainfall data have been smoothed using penalized smoothing according to generalized cross validation criteria. A descriptive statistic of the functional data depicted the mean and variation of the rainfall curve over time, while the functional principal component analysis measured the temporal. The proposed approach of functional principal components has been successfully carried out and demonstrated significant findings for rainfall patterns and temporal variations. The major objective of this study is to adapt the functional principal component analysis (fpca) method for rainfall data to capture the variations over time intervals and establish a functional model of the rainfall patterns.

A Plot The Functional Rainfall Data B Plot The Smoothed Functional The proposed approach of functional principal components has been successfully carried out and demonstrated significant findings for rainfall patterns and temporal variations. The major objective of this study is to adapt the functional principal component analysis (fpca) method for rainfall data to capture the variations over time intervals and establish a functional model of the rainfall patterns. The functional rainfall data have been smoothed using penalized smoothing according to generalized cross validation criteria. A descriptive statistic of the functional data depicted the mean and variation of the rainfall curve over time, while the functional principal component analysis measured the temporal variability of the rainfall curve. The main concern of this study is to build a functional data object from discrete rainfall observations by looking at how rainfall fluctuates, both spatially and temporally, in the form of smoothing curves. In order to capture the wind and rainfall variations, a functional data analysis is introduced. the purpose of this study is to convert the wind and rainfall data into a smooth curve by using functional data analysis method.