R: tsEvaTransformSeriesToStationaryPeakTrend

tsEvaTransformSeriesToStationaryPeakTrend {RtsEva}

R Documentation

tsEvaTransformSeriesToStationaryPeakTrend

Description

tsEvaTransformSeriesToStationaryPeakTrend transforms a time series to a stationary one by focusing on extremes. The trend and slowly varying amplitude are computed on values above a threshold defined by the user or automatically with the function tsEvaFindTrendThreshold.

Usage

tsEvaTransformSeriesToStationaryPeakTrend(
  timeStamps,
  series,
  timeWindow,
  TrendTh
)

Arguments

`timeStamps`	A vector of time stamps corresponding to the observations in the series.
`series`	A vector of the time series data.
`timeWindow`	The size of the time window used for detrending.
`TrendTh`	The threshold for fitting the trend on the means above a given quantile. Default is 0.5.

Value

A list containing the following components:

runningStatsMulteplicity: The multiplicity of running statistics.
stationarySeries: The stationary series after removing the trend.
trendSeries: The trend component of the series.
trendSeriesNonSeasonal: NULL (not used).
trendError: The error on the trend component.
stdDevSeries: The standard deviation series.
stdDevSeriesNonSeasonal: NULL (not used).
stdDevError: The error on the standard deviation series.
timeStamps: The time stamps.
nonStatSeries: The original non-stationary series.
statSer3Mom: The running mean of the third moment of the stationary series.
statSer4Mom: The running mean of the fourth moment of the stationary series.

Examples

timeAndSeries <- ArdecheStMartin
timeStamps <- ArdecheStMartin[,1]
series <- ArdecheStMartin[,2]
#select only the 5 latest years
yrs <- as.integer(format(timeStamps, "%Y"))
tokeep <- which(yrs>=2015)
timeStamps <- timeStamps[tokeep]
series <- series[tokeep]
timeWindow <- 365 # 1 year
TrendTh <- NA
result <- tsEvaTransformSeriesToStationaryPeakTrend(timeStamps,
series, timeWindow, TrendTh)
plot(result$trendSeries)