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Some updates in README file
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mmhs013 committed Jul 26, 2019
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Expand Up @@ -43,23 +43,23 @@ Mann-Kendall Test is a powerful trend test, so several others modified Mann-Kend

All Mann-Kendall test functions have almost similar input parameters. Those are:

- **x**: a vector of data
- **alpha**: significance level (0.05 default)
- **x**: a vector (list, numpy array or pandas series) data
- **alpha**: significance level (0.05 is the default)
- **lag**: No. of First Significant Lags (Only available in hamed_rao_modification_test and yue_wang_modification_test)
- **period**: seasonal cycle. For monthly data it is 12, weekly data it is 52 (Only available in seasonal tests)

And all Mann-Kendall tests return a named tuple which contained:

- **trend**: tells the trend (increasing, decreasing or no trend)
- **h**: True (if trend is present) or False (if trend is absence)
- **p**: p value of the significance test
- **h**: True (if trend is present) or False (if the trend is absence)
- **p**: p-value of the significance test
- **z**: normalized test statistics
- **Tau**: Kendall Tau
- **s**: Mann-Kendal's score
- **var_s**: Variance S
- **slope**: sen's slope

sen's slope function required data vector. seasonal sen's slope also has optional input period, which by default value is 12. Both sen's slope function return only slope value.
sen's slope function required data vector. seasonal sen's slope also has optional input period, which by the default value is 12. Both sen's slope function return only slope value.

## Dependencies

Expand Down Expand Up @@ -152,41 +152,41 @@ If you publish results for which you used `pyMannKendall`, please give credit by

## Contributions

`pyMannKendall` is a community project and welcomes contributions. Additional information can be found in the [contribution guidelines](https://github.com/mmhs013/pyMannKendall/blob/master/CONTRIBUTING.md)
`pyMannKendall` is a community project and welcomes contributions. Additional information can be found in the [contribution guidelines](https://github.com/mmhs013/pyMannKendall/blob/master/CONTRIBUTING.md).


## Code of Conduct

`pyMannKendall` wishes to maintain a positive community. Additional details can be found in the [Code of Conduct](https://github.com/mmhs013/pyMannKendall/blob/master/CODE_OF_CONDUCT.md)
`pyMannKendall` wishes to maintain a positive community. Additional details can be found in the [Code of Conduct](https://github.com/mmhs013/pyMannKendall/blob/master/CODE_OF_CONDUCT.md).


## References

1. Bari,S.H., Rahman,M.T.U., Hoque,M.A., & Hussain,M.M.(2016). Analysis of seasonal and annual rainfall trends in the northern region of Bangladesh. Atmospheric Research, 176, 148–158. doi:[10.1016/j.atmosres.2016.02.008](https://doi.org/10.1016/j.atmosres.2016.02.008)
1. Bari, S. H., Rahman, M. T. U., Hoque, M. A., & Hussain, M. M. (2016). Analysis of seasonal and annual rainfall trends in the northern region of Bangladesh. *Atmospheric Research*, 176, 148–158. doi:[10.1016/j.atmosres.2016.02.008](https://doi.org/10.1016/j.atmosres.2016.02.008)

2. Cox, D. R., & Stuart, A. (1955). Some quick sign tests for trend in location and dispersion. Biometrika, 42(1/2), 80–95. doi:[10.2307/2333424](https://doi.org/10.2307/2333424)
2. Cox, D. R., & Stuart, A. (1955). Some quick sign tests for trend in location and dispersion. *Biometrika*, 42(1/2), 80–95. doi:[10.2307/2333424](https://doi.org/10.2307/2333424)

3. Hamed, K. H., & Rao, A. R. (1998). A modified Mann–Kendall trend test for autocorrelated data. Journal of hydrology, 204(1-4), 182–196. doi:[10.1016/S0022-1694(97)00125-X](https://doi.org/10.1016/S0022-1694(97)00125-X)
3. Hamed, K. H., & Rao, A. R. (1998). A modified Mann–Kendall trend test for autocorrelated data. *Journal of hydrology*, 204(1-4), 182–196. doi:[10.1016/S0022-1694(97)00125-X](https://doi.org/10.1016/S0022-1694(97)00125-X)

4. Helsel, D. R., & Frans, L. M. (2006). Regional Kendall test for trend. Environmental science & technology, 40(13), 4066–4073. doi:[10.1021/es051650b](https://doi.org/10.1021/es051650b)
4. Helsel, D. R., & Frans, L. M. (2006). Regional Kendall test for trend. *Environmental science & technology*, 40(13), 4066–4073. doi:[10.1021/es051650b](https://doi.org/10.1021/es051650b)

5. Hipel, K. W., & McLeod, A. I. (1994). Time series modelling of water resources and environmental systems (Vol. 45). Elsevier.

6. Hirsch, R. M., Slack, J. R., & Smith, R. A. (1982). Techniques of trend analysis for monthly water quality data. Water resources research, 18(1), 107–121. doi:[10.1029/WR018i001p00107](https://doi.org/10.1029/WR018i001p00107)
6. Hirsch, R. M., Slack, J. R., & Smith, R. A. (1982). Techniques of trend analysis for monthly water quality data. *Water resources research*, 18(1), 107–121. doi:[10.1029/WR018i001p00107](https://doi.org/10.1029/WR018i001p00107)

7. Kendall, M. (1975). Rank correlation measures. Charles Griffin, London, 202, 15.
7. Kendall, M. (1975). Rank correlation measures. *Charles Griffin*, London, 202, 15.

8. Libiseller, C., & Grimvall, A. (2002). Performance of partial Mann–Kendall tests for trend detection in the presence of covariates. Environmetrics: The official journal of the International Environmetrics Society, 13(1), 71–84. doi:[10.1002/env.507](https://doi.org/1010.1002/env.507)
8. Libiseller, C., & Grimvall, A. (2002). Performance of partial Mann–Kendall tests for trend detection in the presence of covariates. *Environmetrics: The official journal of the International Environmetrics Society*, 13(1), 71–84. doi:[10.1002/env.507](https://doi.org/1010.1002/env.507)

9. Mann, H. B. (1945). Nonparametric tests against trend. Econometrica: Journal of the Econometric Society, 245–259. doi:[10.2307/1907187](https://doi.org/10.2307/1907187)
9. Mann, H. B. (1945). Nonparametric tests against trend. *Econometrica: Journal of the Econometric Society*, 245–259. doi:[10.2307/1907187](https://doi.org/10.2307/1907187)

10. Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall’s tau. Journal of the American statistical association, 63(324), 1379–1389. doi:[10.1080/01621459.1968.10480934](https://doi.org/10.1080/01621459.1968.10480934)
10. Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall’s tau. *Journal of the American statistical association*, 63(324), 1379–1389. doi:[10.1080/01621459.1968.10480934](https://doi.org/10.1080/01621459.1968.10480934)

11. Theil,H.(1950). A rank-invariant method of linear and polynominal regression analysis (parts 1-3). In Ned. Akad. Wetensch. Proc. Ser. A (Vol. 53, pp. 1397–1412).
11. Theil, H. (1950). A rank-invariant method of linear and polynominal regression analysis (parts 1-3). In *Ned. Akad. Wetensch. Proc. Ser. A* (Vol. 53, pp. 1397–1412).

12. Yue, S., & Wang, C. (2004). The Mann–Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water resources management, 18(3), 201–218. doi:[10.1023/B:WARM.0000043140.61082.60](https://doi.org/10.1023/B:WARM.0000043140.61082.60)
12. Yue, S., & Wang, C. (2004). The Mann–Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. *Water resources management*, 18(3), 201–218. doi:[10.1023/B:WARM.0000043140.61082.60](https://doi.org/10.1023/B:WARM.0000043140.61082.60)

13. Yue, S., & Wang, C. Y. (2002). Applicability of prewhitening to eliminate the influence of serial correlation on the Mann–Kendall test. Water resources research, 38(6), 4–1. doi:[10.1029/2001WR000861](https://doi.org/10.1029/2001WR000861)
13. Yue, S., & Wang, C. Y. (2002). Applicability of prewhitening to eliminate the influence of serial correlation on the Mann–Kendall test. *Water resources research*, 38(6), 4–1. doi:[10.1029/2001WR000861](https://doi.org/10.1029/2001WR000861)

14. Yue, S., Pilon, P., Phinney, B., & Cavadias, G. (2002). The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrological processes, 16(9), 1807–1829. doi:[10.1002/hyp.1095](https://doi.org/10.1002/hyp.1095)
14. Yue, S., Pilon, P., Phinney, B., & Cavadias, G. (2002). The influence of autocorrelation on the ability to detect trend in hydrological series. *Hydrological processes*, 16(9), 1807–1829. doi:[10.1002/hyp.1095](https://doi.org/10.1002/hyp.1095)

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