tsEvaTransformSeriesToStationaryTrendOnly

<code>tsEvaTransformSeriesToStationaryTrendOnly</code> is the original detrending
function implemented in Mentaschi et al.(2016).
It takes a time series and transforms it into a stationary one.
It computes the trend as a running average of the time series,
the slowly varying amplitude as its standard deviation, and other statistical measures.

Adaptation of the 'Matlab' 'tsEVA' toolbox developed by Lorenzo Mentaschi
available here:
<https://github.com/menta78/tsEva>. It contains an implementation of the
Transformed-Stationary (TS) methodology for non-stationary extreme
value Analysis (EVA) as described in Mentaschi et al. (2016) <doi:10.5194/hess-20-3527-2016>.
In synthesis this approach consists in:
(i) transforming a non-stationary time series into a
stationary one to which the stationary extreme value theory can be applied; and
(ii) reverse-transforming the result into a non-stationary extreme
value distribution.
'RtsEva' offers several options for trend estimation (mean, extremes, seasonal)
and contains multiple plotting functions displaying different aspects
of the non-stationarity of extremes.

Alois Tilloy

RtsEva

Performs the Transformed-Stationary Extreme Values Analysis

tsEvaTransformSeriesToStationaryTrendOnly function

<dl><dt>timeStamps</dt>
<dd>A vector of time stamps for the time series.</dd>
<dt>series</dt>
<dd>The original time series.</dd>
<dt>timeWindow</dt>
<dd>The size of the time window used for detrending.</dd></dl>

Arguments

tsEvaTransformSeriesToStationaryTrendOnly — tsEvaTransformSeriesToStationaryTrendOnly

<dl>

<dt>timeStamps</dt>
<dd>A vector of time stamps for the time series.</dd>


<dt>series</dt>
<dd>The original time series.</dd>


<dt>timeWindow</dt>
<dd>The size of the time window used for detrending.</dd>

</dl>

tsEvaTransformSeriesToStationaryTrendOnly: tsEvaTransformSeriesToStationaryTrendOnly

Description

Usage

Value

Arguments

Examples