evalRobustness.BBackTesting: Evaluating the Robustness of the Forecasting Mortality Models

In mpascariu/MortalityForecast: Standard Tools to Compare and Evaluate Various Mortality Forecasting Methods

Description

Evaluating the Robustness of the Forecasting Mortality Models

Usage

## S3 method for class 'BBackTesting'
evalRobustness(object, data.out = c("qx", "mx",
  "dx", "lx", "Lx", "Tx", "ex"), measures = c("MD", "MAD", "sMRAD",
  "MASD"), ...)

Arguments

object	An object of class BBackTesting.
data.out	Specify the type of data to be returned in output. Various life table indices are accepted: "qx", "mx", "dx", "lx", "Lx", "Tx", "ex".
measures	What accuracy measure to compute? Various alternatives are available, Mean error measures: "ME", "MAE", "MAPE", "sMAPE", "sMRAE", "MASE"; Median error measures: "MdE", "MdAE", "MdAPE", "sMdAPE", "sMdRAE", "MdASE"; Squared error measures: "MSE", "RMSE", "RMSPE", "RMdSPE"; Geometric mean measure for positive errors: "GMRAE". If measures = NULL all the measures will be computed.
...	Arguments to be passed to or from other methods.

Author(s)

Marius D. Pascariu

See Also

do.BBackTesting evalAccuracy.BBackTesting

Examples

# For examples go to ?do.BBackTesting

mpascariu/MortalityForecast documentation built on Sept. 28, 2020, 2:40 p.m.