predict.WH_2d

Extrapolate the Whittaker-Henderson fit for new observations in a way that is
consistent with the initial model fit.

An enhanced implementation of Whittaker-Henderson smoothing for the gradation
of one-dimensional and two-dimensional actuarial tables used to quantify Life Insurance risks.
'WH' is based on the methods described in Biessy (2023) <doi:10.48550/arXiv.2306.06932>.
Among other features, it generalizes the original smoothing algorithm to maximum likelihood estimation,
automatically selects the smoothing parameter(s) and extrapolates beyond the range of data.

Guillaume Biessy

Enhanced Implementation of Whittaker-Henderson Smoothing

predict.WH_2d function

<dl><dt>object</dt>
<dd>An object of class <code>"WH_2d"</code> returned by the <code>WH_2d()</code> function</dd>
<dt>newdata</dt>
<dd>A list containing two vectors indicating the new observation
positions</dd>
<dt>...</dt>
<dd>Not used</dd></dl>

Arguments

Prediction for a Whittaker-Henderson Fit — predict.WH_2d

<dl>

<dt>object</dt>
<dd>An object of class <code>"WH_2d"</code> returned by the <code>WH_2d()</code> function</dd>


<dt>newdata</dt>
<dd>A list containing two vectors indicating the new observation
positions</dd>


<dt>...</dt>
<dd>Not used</dd>

</dl>

predict.WH_2d: Prediction for a Whittaker-Henderson Fit

Description

Usage

Value

Arguments

Examples