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Makes univariate, multivariate, or random fields simulations precise and simple. Just select the desired time series or random fields’ properties and it will do the rest. CoSMoS is based on the framework described in Papalexiou (2018, <doi:10.1016/j.advwatres.2018.02.013>), extended for random fields in Papalexiou and Serinaldi (2020, <doi:10.1029/2019WR026331>), and further advanced in Papalexiou et al. (2021, <doi:10.1029/2020WR029466>) to allow fine-scale space-time simulation of storms (or even cyclone-mimicking fields).

Kevin Shook

CoSMoS

Complete Stochastic Modelling Solution

Simon Michael Papalexiou

Francesco Serinaldi

Filip Strnad

Yannis Markonis

MSE function

<dl><dt>x</dt>
<dd>numeric vector of observed values</dd>
<dt>y</dt>
<dd>numeric vector of reference values</dd></dl>

Arguments

Mean squared error — MSE

<dl>

<dt>x</dt>
<dd>numeric vector of observed values</dd>


<dt>y</dt>
<dd>numeric vector of reference values</dd>

</dl>

Mean squared error

MSE: Mean squared error

Description

Usage

Value

Arguments

See Also