modifiedmk (version 1.6)

mmky1lag: Modified Mann-Kendall Test For Serially Correlated Data Using the Yue and Wang (2004) Variance Correction Approach Using the Lag-1 Correlation Coefficient Only

Description

Time series data is often influenced by serial correlation. When data are not random and influenced by autocorrelation, modified Mann-Kendall tests may be used for trend detction. Yue and Wang (2004) have proposed a variance correction approach to address the issue of serial correlation in trend analysis. Data are initially detrended and the effective sample size is calculated using the lag-1 autocorrelation coefficient.

Usage

mmky1lag(x)

Arguments

x

- Time series data vector

Value

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

Details

The variance correction approach suggested by Yue and Wang (2004) is implemeted in this function. Effective sample size is calculated based on the AR(1) assumption.

References

Kendall, M. (1975). Rank Correlation Methods. Griffin, London, 202 pp.

Mann, H. B. (1945). Nonparametric Tests Against Trend. Econometrica, 13(3): 245-259.

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. <doi:10.2307/2285891>

Yue, S. and 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. <doi:10.1023/B:WARM.0000043140.61082.60>

Examples

# NOT RUN {
x<-c(Nile)
mmky1lag(x)

# }