tsEvaNanRunningMean

This function calculates the running mean of a time series, taking into account NaN values.
It uses a sliding window approach to calculate the mean, where the window size is specified by the user.
If the number of non-NaN values within the window is greater than a threshold, the mean is calculated.
Otherwise, NaN is returned.

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

tsEvaNanRunningMean function

<dl><dt>series</dt>
<dd>The input time series</dd>
<dt>windowSize</dt>
<dd>The size of the sliding window</dd></dl>

Arguments

Calculate the running mean of a time series with NaN handling — tsEvaNanRunningMean

<dl>

<dt>series</dt>
<dd>The input time series</dd>


<dt>windowSize</dt>
<dd>The size of the sliding window</dd>

</dl>

tsEvaNanRunningMean: Calculate the running mean of a time series with NaN handling

Description

Usage

Value

Arguments

Examples