tsEvaTransformSeriesToStationaryTrendOnly_ciPercentile {RtsEva}

tsEvaTransformSeriesToStationaryTrendOnly_ciPercentile

Description

tsEvaTransformSeriesToStationaryTrendOnly_ciPercentile transforms a time series to a stationary ones using a moving average as the trend and a running percentiles to represent the slowly varying amplitude of the distribution

Usage

tsEvaTransformSeriesToStationaryTrendOnly_ciPercentile(
  timeStamps,
  series,
  timeWindow,
  percentile
)

Arguments

timeStamps

A vector of time stamps for the time series.

series

The original time series.

timeWindow

The size of the moving window used for detrending.

percentile

The percentile value used to compute the extreme trend of the stationary series.

Value

A list containing the following elements:

runningStatsMulteplicity

The running statistics multiplicity

stationarySeries

The transformed stationary trend only series

trendSeries

The trend series

trendSeriesNonSeasonal

The non-seasonal trend series

trendError

The error on the trend

stdDevSeries

The standard deviation series

stdDevSeriesNonSeasonal

The non-seasonal standard deviation series

stdDevError

The error on the standard deviation

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
percentile <- 90
result <- tsEvaTransformSeriesToStationaryTrendOnly_ciPercentile(timeStamps,
series, timeWindow, percentile)
plot(result$trendSeries)