pyHomogeneity: A Python Package for Homogeneity Test of Time Series Data
References
- XLSTAT: The Leading Data analysis and statistical solution for Microsoft Excel. [Online]. Available:
https://www.xlstat.com/en/ . - Pohlert T. Trend: Non-parametric trend tests and change-point detection; 2016. Available:
https://cran.r-project.org/web/packages/trend/index.html . - Dey P. Pettitt Change point test for univariate time series data. MATLAB Central File Exchange; 2022. Available:
https://www.mathworks.com/matlabcentral/fileexchange/60973-pettitt-change-point-test-for-univariate-time-series-data . - NumPy, fundamental package for scientific computing with Python. [Online]. Available:
http://www.numpy.org/ . - SciPy, Python-based ecosystem of open-source software. [Online]. Available:
https://www.scipy.org/ . - Pettitt A. A non-parametric approach to the change-point problem. Journal of the Royal Statistical Society: Series C (Applied Statistics). 1979; 28(2): 126–135. DOI: 10.2307/2346729
- Alexandersson H. A homogeneity test applied to precipitation data. Journal of Climatology. 1986; 6(6): 661–675. DOI: 10.1002/joc.3370060607
- Mahmud I, Bari SH, Hussain MM, Rahman MT. Homogeneity of rainfall and temparature series in bangladesh. International Conference on Climate Change and Water Security; 2015. DOI: 10.13140/RG.2.1.4431.3688
- Buishand TA. Some methods for testing the homogeneity of rainfall records. Journal of Hydrology. 1982; 58(1–2): 11–27. DOI: 10.1016/0022-1694(82)90066-X
- Buishand TA. Tests for detecting a shift in the mean of hydrological time series. Journal of Hydrology. 1984; 73(1–2): 51–69. DOI: 10.1016/0022-1694(84)90032-5
- Travis CI, continuous integration service used to build and test software projects hosted on GitHub and Bitbucket. [Online] Available:
https://www.travis-ci.com/ . - Talukder MR. Analyzing trend and prediction of precipitation in Germany using non-parametrical tests and machine learning algorithms. ScienceOpen Preprints; Nov 21 2021. DOI: 10.14293/S2199-1006.1.SOR-.PPCPS00.v1
- Parajuli B, Zhang X, Deuja S, Liu Y. Regional and Seasonal Precipitation and Drought Trends in Ganga–Brahmaputra Basin. Water. Jan 2021; 13(16): 2218. DOI: 10.3390/w13162218
- Li ZH, Wang JX, Lu M, Zhang T, Wang XC, Li WW, Yu HQ. Hospital sewage treatment facilities witness the fighting against the COVID-19 pandemic. Journal of environmental management. May 1 2022; 309: 114728. DOI: 10.1016/j.jenvman.2022.114728
- Dibike Y, Hartmann J, de Rham L, Beltaos S, Peters DL, Bonsal B.
Exploratory Data Analysis of the Canadian River Ice Database Variables and their Correlations with Seasonal Temperature . 21st Workshop on the Hydraulics of Ice Covered Rivers Saskatoon, Saskatchewan, Canada; 2021.
DOI: https://doi.org/10.5334/jors.427 | Journal eISSN: 2049-9647
Language: English
Submitted on: Apr 17, 2022
Accepted on: Jan 25, 2023
Published on: Feb 14, 2023
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
© 2023 Md. Manjurul Hussain, Ishtiak Mahmud, Sheikh Hefzul Bari, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.