Pearson.Bias.Adj.MACK.Full: Pearson.Bias.Adj.MACK.Full

In EduardoRamosP/MackNet: Mack-Net model: Blending Mack's model with Recurrent Neural Networks

Description

It generates the bias adjusted residuals needed for the boostrap implementation of MackNet

Usage

Pearson.Bias.Adj.MACK.Full(Pearson.Resid, Constant.Param)

Arguments

Pearson.Resid

Non-scaled residuals.

Constant.Param

If this variable is set to 0, the bias adjustment suggested by England y Verrall (2006) in "Predictive Distributions of Outstanding Liabilities in General Insurance" is applied, this means that residuals are multiplied by N/(N-p). In case this variable is set to 1, the adjustment suggested by Mack (1993) in "Distribution-free calculation of the standard error of chain ladder reserve estimates" is applied, this means that residuals are multiplied by n(i)/(n(i)-1). Finally, if this variable is set to 2, no adjustment is applied.

Value

Bias adjusted residuals of the MackNet model. These residuals are used within the boostrap procedure.

EduardoRamosP/MackNet documentation built on Sept. 26, 2020, 9:21 a.m.