Trend Analysis:
Kendall's tau
kendall
Calculate Kendall's tau.
Syntax
[tau,p] = kendall (date,conc)
Description
[tau,p] = kendall (date,conc) returns Kendall's tau correlation value of time series [date,conc] (N by 1 vectors), also returns p, the p-values of Kendall's tau correlation. If p is small, say less than 0.05, then the Kendall's tau is statistical significant.
Calculate Kendall's tau.
Syntax
[tau,p] = kendall (date,conc)
Description
[tau,p] = kendall (date,conc) returns Kendall's tau correlation value of time series [date,conc] (N by 1 vectors), also returns p, the p-values of Kendall's tau correlation. If p is small, say less than 0.05, then the Kendall's tau is statistical significant.
Sen's Slope
sen
Calculate Sen's slope and intercept.
Syntax
[slope,intercept] = sen (date,conc,plot)
Description
[slope,intercept] = sen (date,conc,plot) returns the slope and intercept of time series [date,conc] (N by 1 vectors) by Sen's slope estimator. Figure will be plotted compared with the result of regular linear regression if plot equals 1.
Calculate Sen's slope and intercept.
Syntax
[slope,intercept] = sen (date,conc,plot)
Description
[slope,intercept] = sen (date,conc,plot) returns the slope and intercept of time series [date,conc] (N by 1 vectors) by Sen's slope estimator. Figure will be plotted compared with the result of regular linear regression if plot equals 1.