The Mann-Kendall test is for detecting either an upward or downward trend in data collected over time.I suggest you to use MINITAB software which gives you enough analysis information.
Mann-Kendall test is a non-parametric trend test which can be used to detect the trend in meteorological time series like precipitation, or other time series. Non-parametric tests do not require the data-set to be normally distributed.
It shows the statistical significance of the identified trend on different confidence levels, by calculating an index called z-score. Sign of the z-score shows the direction of the trend and higher the value of it, higher the confidence level of the statistical significance of the trend.
If you are using MATLAB, you can use this code for the calculations:
Could you please show to math function of excel in MAKESENS file, especially Trend statistic as step by step how to find each value, because I do need to do my study as fast as possible. please help me to solve this problem.
I had a question. I used mmkh function of modified mann-kendall package. But it is giving the same result as mkttest function of mann-kendall package. But in the help pages it is written that mkttest is man kendall test without any modification while mmkh should be the modified mankendall test jsed by Hamed and Rao (1998). So if there is autocorrelation the results should be different.
please answer my question. I am badly in need of this answer.
I have uploaded a CRAN package named 'modifiedmk' please check if you get solution using the package. Tutorial is also available as a word document for the package in my profile (may be as a project update)!
Thank you so much for your quick response Sir. Here I uploaded my serially correlated data set bin.csv and the screenshots of the results I found using mkttest and mmkh functions. This data set has lag 1 autocorrelation. I have checked it earlier. So according to my knowledge mkttest is mann kendall test without any autocorrelation correction and mmkh introduced by Hamid and Rao is a modified mann Kendal test which can remove complete serial correlation of the data set. So according to this knowledge the results of Z should be different. But here the results I found using mkttest and mmkh are the same.
It is perfectly normal in some cases. Variance of the data doesn't change even after variance correction.
It is not an error. You can proceed further with your analysis. Also, if you like, you can use mmkh3lag as first three lags are considered in many studies (refer the citation in the help file)
John...please refer to literature. In modified Mann Kendall test, we try to eliminate the effects if Auto correaltion in the days and there are more than one way of doing it. Hence there is no single version if modified Mann-kendall test. There are a few ways if doing it. Refer any standard review paper for further details.
before performing Modified mann kendall test should i apply auto correlation on my time series data or directly i should apply the test on raw data.. and how should i interpret the result for trend. KIndly help
Sir i did auto correlation first.and then have applied mann kendall test using mmkh function in R .. Now how should i interpret my results ... Literature says if values of p is less than 0.05 then that Z values will tell you regarding trend ...
Vishal Sharma Please refer to the attached publication. Also, I would suggest checking the data for Homogeneity before performing climatological analysis.
Article Long-Term Homogeneity, Trend, and Change-Point Analysis of R...
Sandeep Kumar Patakamuri Dear sir, I know about that link which one you shared. I already have performed Mann Kendall trend test for raster data. I asked you , how to perform Modified Mann Kendall trend test for raster data?