xNetSubscribe

<p>An illustrative dataset---a matrix (of the dimensions 12<code>x</code>12) with a
monthly-based income (in EUR) of a local internet data provider with the
income structured by the customers subscribing  within the given month (in 2023)
reported in the rows and monthly-based payments reported in columns.
The data matrix represents the incremental type of the run-off triangle.</p>

Functional claims reserving methods based on aggregated chain-ladder data, also known as a run-off triangle, implemented in three nonparametric algorithms (PARALLAX, REACT, and MACRAME) proposed in Maciak, Mizera, and Pešta (2022) <doi:10.1017/asb.2022.4>. Additional methods including permutation bootstrap for completed run-off triangles are also provided.

Matúš Maciak

ProfileLadder

Functional-Based Chain Ladder for Claims Reserving

Rastislav Matúš

Ivan Mizera

Michal Pešta

xNetSubscribe function


<div class="section" id="xnetsubscribe">
<h3>xNetSubscribe</h3><p></p><p>
</p><p>A simple <code>12x12</code> (trangular) matrix of the class <code>triangle</code> with
twelve consecutive months (January 2023 -- December 2023) when new customers
subscribed to the stream service (rows) and monthly-based payments (columns)</p>
</div>


Format

Internet Provider Monthly Income Data — xNetSubscribe


<div class='section' id='xnetsubscribe'>
<h3>xNetSubscribe</h3>


<p>A simple <code>12x12</code> (trangular) matrix of the class <code>triangle</code> with
twelve consecutive months (January 2023 -- December 2023) when new customers
subscribed to the stream service (rows) and monthly-based payments (columns)</p>
</div>


xNetSubscribe: Internet Provider Monthly Income Data

Description

Usage

Arguments

Format

xNetSubscribe