Computes one of four fitting norms used as the objective function in
<code>fitDist</code>.

internal

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

N function

<dl><dt>par</dt>
<dd>numeric vector of distribution parameter values</dd>
<dt>val</dt>
<dd>numeric vector of empirical data</dd>
<dt>dist</dt>
<dd>character; name of the distribution to fit (e.g. <code>"norm"</code>,
<code>"ggamma"</code>)</dd>
<dt>norm</dt>
<dd>character; norm identifier — one of <code>"N1"</code>, <code>"N2"</code>,
<code>"N3"</code>, <code>"N4"</code></dd>
<dt>n.points</dt>
<dd>integer; number of ECDF points used in the norm computation</dd></dl>

Arguments

Norm minimised during distribution fitting — N

<dl>

<dt>par</dt>
<dd>numeric vector of distribution parameter values</dd>


<dt>val</dt>
<dd>numeric vector of empirical data</dd>


<dt>dist</dt>
<dd>character; name of the distribution to fit (e.g. <code>"norm"</code>,
<code>"ggamma"</code>)</dd>


<dt>norm</dt>
<dd>character; norm identifier — one of <code>"N1"</code>, <code>"N2"</code>,
<code>"N3"</code>, <code>"N4"</code></dd>


<dt>n.points</dt>
<dd>integer; number of ECDF points used in the norm computation</dd>

</dl>

N: Norm minimised during distribution fitting

Description

Usage

Value

Arguments

See Also