A modified box and cox power transformation to determine the standardized precipitation index
© 2018, Prince of Songkla University. All rights reserved. The objective of this research was to create a new transformation method, based on a modification of the Box and Cox power transformation (SMBC) by adding the ratio of skewness to two sample sizes, to characterized rought conditions with a s...
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| Main Authors: | , |
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| Format: | Journal |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85057187948&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/62988 |
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| Institution: | Chiang Mai University |
| Summary: | © 2018, Prince of Songkla University. All rights reserved. The objective of this research was to create a new transformation method, based on a modification of the Box and Cox power transformation (SMBC) by adding the ratio of skewness to two sample sizes, to characterized rought conditions with a standardized precipitation index (SPI). Along with the various classical data transformations, namely the Box and Cox power transformation (BC), the exponential transformation, the Yeo and Johnson transformation, and a modification to BC by adding range, the results of a simulation study showed that the BC and SMBC methods had similar efficiencies when transforming gamma data, Weibull data, and Pearson type III data to a normal distribution, and notably, SMBC performed particularly well with the latter. Drought conditions were evaluated using the SMBC transformation on real-life data from rain gauging stations at Muang (Lamphun), Mae Prik (Lampang) and Chom Thong (Chiang Mai), Thailand. The SMBC proved to be particularly useful in determining the SPI. |
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