mmky: Modified Mann-Kendall Test For Serially Correlated Data Using...

Description Usage Arguments Details Value References Examples

View source: R/mmky.R

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 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 significant serial correlation coefficients.

Usage

1

Arguments

x

- Time series data vector

Details

The variance correction approach suggested by Yue and Wang (2004) is implemeted in this function. Serial correlation coefficients for all lags are used in calculating the effective sample size.

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

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’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): 201–218. <doi:10.1023/B:WARM.0000043140.61082.60>

Examples

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x<-c(Nile)
mmky(x)

modifiedmk documentation built on June 10, 2021, 9:09 a.m.