CVA: Coefficient of variation analysis
In lfduquey/IETD: Inter-Event Time Definition

Description Usage Arguments Details Value Note Author(s) References Examples

View source: R/CVA.R

This function computes the inter-event time definition (IETD) based on the coefficient of variation analysis.

1	CVA(Time_series,MaxIETD,xlabel,ylabel)

`Time_series`	A dataframe. The first column contains the time and day of a rainfall pulse and the second one the depth of rainfall in each time step. The date must be as POSIXct class.
`MaxIETD`	The maximum value of IETD to be analyzed (in hours). Default value 24.
`xlabel`	Label of the x-axis of the figure IETD vs CV.
`ylabel`	Label of the y-axis of the figure IETD vs CV.

This method assumes that inter-event times (b) are represented well by a exponential distribution. Since by definition b>= IETD, IETD is computed as the value whose resulting coefficient of variation (CV) of b equal to unity \insertCiteRestrepo-Posada1982,Adams2000IETD. This analysis is done by testing several values of IETD and analyzing the resulting CV. The computed IETD is obtained via interpolation from the figure of IETD vs CV.

A list with a figure of IETD vs CV, a dataframe with the values of that figure, and the computed value of IETD.

To review the concepts of b and IETD, go to the details of drawre function.

Luis F. Duque <lfduquey@gmail.com> <l.f.duque-yaguache2@newcastle.ac.uk>

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