runmax

dfrunmax

Running \(n\)-value maximum and data frame with variable swapped for running maximum

Methods for fitting various extreme value distributions with parameters of
generalised additive model (GAM) form are provided. For details of distributions
see Coles, S.G. (2001) <doi:10.1007/978-1-4471-3675-0>, GAMs see Wood, S.N. (2017)
<doi:10.1201/9781315370279>, and the fitting approach see Wood, S.N., Pya, N. &
Safken, B. (2016) <doi:10.1080/01621459.2016.1180986>. Details of how evgam works
and various examples are given in Youngman, B.D. (2022) <doi:10.18637/jss.v103.i03>.

Ben Youngman

evgam

Generalised Additive Extreme Value Models

runmax function

<dl><dt>y</dt>
<dd>a vector</dd>
<dt>n</dt>
<dd>an integer giving the number of observations to calculate running maxmimum over; defaults to 2</dd>
<dt>data</dt>
<dd>a data frame</dd>
<dt>cons</dt>
<dd>a character string for the variable in <code>data</code> that identifies consecutive observations</dd>
<dt>ynm</dt>
<dd>a character string for the variable in <code>data</code> that is the observations</dd></dl>

Arguments

Running maximum — runmax

<dl>

<dt>y</dt>
<dd>a vector</dd>


<dt>n</dt>
<dd>an integer giving the number of observations to calculate running maxmimum over; defaults to 2</dd>


<dt>data</dt>
<dd>a data frame</dd>


<dt>cons</dt>
<dd>a character string for the variable in <code>data</code> that identifies consecutive observations</dd>


<dt>ynm</dt>
<dd>a character string for the variable in <code>data</code> that is the observations</dd>

</dl>

runmax: Running maximum

Description

Usage

Value

Arguments

Examples