Renext (version 3.1-4)

interevt: Interevents (or interarrivals) from events dates

Description

Compute intervent durations from events dates

Usage

interevt(date,
            skip = NULL, noskip = NULL)

Value

A list mainly containing a interevt data.frame.

interevt

Data.frame. Each row describes a retained interevent through a period integer giving the "noskip" period, a start and end POSIXct and a duration in days.

noskip

Only when skip or noskip args have been given. A data.frame containing broadly the same information as the noskip arg is it was given or the information deduced from the skip arg if given.

axis

When needed, a list with some material to build an axis with uneven ticks as in the gof.date with skip.action = "omit".

Arguments

date

A POSIXct vector containing the date(time) of the events.

skip

A data.frame containing two POSIXct columns start and end describing the periods to skip over.

noskip

A data.frame like skip but where the periods define the NON skipped part of the events.

Author

Yves Deville

Details

Interevents are the time differences between successive dates. When the date argument contains occurrence times \(T_i\) for successive events of an homogeneous Poisson process, interevents \(T_i -T_{i-1}\) are mutually independent with the same exponential distribution.

When some time intervals are skipped independently from the event point process, we may consider the interevents \(T_i-T_{i-1}\) between two non-skipped events such that the time interval \((T_{i-1},\,T_i)\) does not contains any skipped interval. These interevents still are mutually independent with the same exponential distribution. When skip or noskip is not NULL the computation therefore only retains couples of two successive datetimes "falling" in the same non-skipped period, which number can therefore be associated with the interevent.

See Also

gof.date for goodness-of-fit diagnostics for dates of events expplot for diagnostics concerning the exponential distribution.

Examples

## Use Brest data
ie <- interevt(date = Brest$OTdata$date, skip = Brest$OTmissing)

expplot(ie$interevt$duration, rate = 1 / mean(ie$interevt$duration),
  main = "No threshold")

## keep only data over a threshold
ind1 <- Brest$OTdata$Surge >= 35
ie1 <- interevt(Brest$OTdata$date[ind1], skip = Brest$OTmissing)
expplot(ie1$interevt$duration, main = "Threshold = 35")

## increase threshold
ind2 <- Brest$OTdata$Surge >= 55
ie2 <- interevt(date = Brest$OTdata$date[ind2], skip = Brest$OTmissing)
expplot(ie2$interevt$duration, main = "Threshold = 55 cm")