Time series data is often influenced by serial-correlation. When data is not random and influenced by auto-correlation, Modified Mann-Kendall tests are to be used in trend detction. Yue and Wang (2004) have proposed variance correction approach to address the issue of serial correlation in Trend analysis. Trend is removed from the series and effective sample size is calculated using significant serial correlation coefficients.
mmky(x)
- Time series data vector
Corrected Zc - Z-Statistic after variance Correction
new P.value - P-Value after variance correction
N/N* - Effective sample size
Original Z - Original Mann-Kendall Z-Statistic
Old P-value - Original Mann-Kendall P-Value
Tau - Mann-Kendall's Tau
Sen's Slope - Sen's slope
old.variance - Old variance before variance Correction
new.variance - Variance after correction
Mann, H. B. (1945). Nonparametric Tests Against Trend. Econometrica, 13(3), 245<U+2013>259. http://doi.org/10.1017/CBO9781107415324.004
Kendall, M. (1975). Multivariate analysis. Charles Griffin. Londres. 0-85264-234-2.
Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall<U+2019>s Tau. Journal of the American Statistical Association, 63(324), 1379. http://doi.org/10.2307/2285891
Yue, S., & Wang, C. Y. (2004). The Mann-Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resources Management, 18(3), 201<U+2013>218. http://doi.org/10.1023/B:WARM.0000043140.61082.60
# NOT RUN {
x<-c(Nile)
mmky(x)
# }
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