pyMannKendall
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mmhs013
A python package for non parametric Mann Kendall family of trend tests.
Hi, I've been using your library to perform several MK tests and may have found a missing term in the function _correlated_multivariate_test()_. According to [Hipel & McLeod](https://www.elsevier.com/books/time-series-modelling-of-water-resources-and-environmental-systems/hipel/978-0-444-89270-6) (1994) for a...
Hi! Thank you for your M-K package! you define the sen's estimator by this: d[idx : idx + len(j)] = (x[j] - x[i]) / (j - I). But when I...
Add new features in the next version : - [x] Add intercept in sen's slope results as well as other test results. - [x] Add more missing value analysis methods....
Can't use pyMannKendall when the sequence has high autocorrelation? **Based on (modified over-whitening,MOW) Mann-Kendall (M-K) seems to solve this problem, but I will not write code!**
Based on (modified over-whitening,MOW) Mann-Kendall (M-K) trend test method for trend test. **over-whitening Mann-Kendall** and **modified over-whitening Mann-Kendall**????????????????????????????????????? **How to do it?**
I'm running a modified MK test on a couple of short time series: import pymannkendall as mk series1 = [0.41625778, 0.40488883, 0.43044564, 0.44369687, 0.46613348, 0.44420775, 0.45091315, 0.48484614, 0.40252088, 0.43944978, 0.51613973,...
Hi! I recently ran into an issue trying to use the original_test function on some time series data. Here is the error message: in __preprocessing(x) 18 def __preprocessing(x): ---> 19...
