Prediction of missing data in rainfall dataset by using simple statistical method

Prediction of missing data in rainfall dataset by using simple statistical method

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Almost all of the data obtained from hydrological station contains missing data. Usually, this problem occurs due to equipment failures, maintenance work and human error. Incomplete dataset will reduce the ability of a statistical analysis and can cause a bias estimation due to systematic difference...

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Bibliographic Details
Main Authors: Amat R.C (Author), Ibrahim N.M (Author), Izhar T.N.T (Author), Mohd Jafri, I.A (Author), Noor N.M (Author), Noor, N.M (Author), Rahim N.L (Author), Suwardi, A. (Author), Ting S.S (Author), Ul-Saufie, A.Z (Author), Yusof S.Y (Author), Zakarya I.A (Author)
Format: Article
Language:English
Published: IOP Publishing Ltd, 2020
Subjects:
Descriptive statistics
Environmental technology
Errors
Forecasting
Index of agreements
Interpolation
Linear Interpolation
Mean square error
Monitoring stations
Performance indicators
Prediction accuracy
Rain
Root mean squared errors
Social sciences computing
Statistical packages
Statistics
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