https://github.com/adisen99/msc_project
Code, functions and notebooks used for my Masters Project/Thesis.
https://github.com/adisen99/msc_project
master precipitation python statistics thesis
Last synced: about 2 months ago
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Code, functions and notebooks used for my Masters Project/Thesis.
- Host: GitHub
- URL: https://github.com/adisen99/msc_project
- Owner: adisen99
- License: mit
- Created: 2021-09-12T10:23:47.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2023-01-05T11:25:01.000Z (over 3 years ago)
- Last Synced: 2024-04-24T12:05:36.146Z (about 2 years ago)
- Topics: master, precipitation, python, statistics, thesis
- Language: Jupyter Notebook
- Homepage:
- Size: 8.91 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# msc_project
Code, functions and notebooks used for my Masters Project/Thesis.
### Some useful resources for -
#### data binning technique
- http://xarray.pydata.org/en/stable/user-guide/reshaping.html?highlight=stack#stack-and-unstack [READ THIS for refactoring]
- https://groups.google.com/g/xarray/c/fz7HHgpgwk0/m/h0umDBIHAAAJ [related to the link above]
- https://www.saedsayad.com/unsupervised_binning.htm
- https://www.statology.org/equal-frequency-binning-python/
- https://stackoverflow.com/questions/56485160/xarray-equivalent-of-pandas-qcut-function
#### Quantile-Regression
- The theory behind the pseudo R-squared is here - https://stats.stackexchange.com/questions/129200/r-squared-in-quantile-regression
#### Miscellaneous -
- https://scitools.org.uk/cartopy/docs/latest/gallery/lines_and_polygons/features.html?highlight=cfeatures#sphx-glr-download-gallery-lines-and-polygons-features-py (Cartopy features and coastlines)
- https://stats.stackexchange.com/questions/129200/r-squared-in-quantile-regression (**Local measure of goodness for quantreg**)
- https://towardsdatascience.com/calculating-confidence-interval-with-bootstrapping-872c657c058d (Bootstrap confidence interval calculation)
### TODO -
#### Priority
- [ ] Implementation of Dynamic and Thermodynamic Effects
- [ ] Inter-annual variability
- [ ] Precip-temp varying plot in regions of dipole behavior
- [ ] Complete winter season binning
- [x] Repeat the regridding using the `conservative` method which is recommended for upscaling using `xesmf` - The `conservative` method is not working so sticking to the `bilinear` method. The difference of the output is quite low.
#### If time available
- [ ] Implement quantile regression as an alternative regressor and also the ZM method from Ali 2018 paper and compare the time and results with the binning method. Link to the technique - click [here](https://www.statology.org/quantile-regression-in-python/) and [here](https://subramgo.github.io/2017/03/13/Quantile-Regression/) or using SKlearn. (NOT DOING)
- [ ] Figure out the use of finding Block maxima and Climate change Indices - Resources -'
https://search.brave.com/search?q=calculate+block+maxima+python&source=desktop
https://pypi.org/project/evt/
https://kikocorreoso.github.io/scikit-extremes/index.html
http://etccdi.pacificclimate.org/list_27_indices.shtml
https://search.brave.com/search?q=calculation+of+climate+change+indices&source=desktop