data_summarised: Sample mortality data stratified by insurance products
In BayesMoFo: Bayesian Mortality Forecasting

data_summarised

R Documentation

Sample mortality data stratified by insurance products

Description

This is a sample data set used for demonstration purposes.

Usage

data("data_summarised")

Format

A data frame with 1278 rows of observations and 9 variables:

Product: Character. The name of the insurance product associated with the observation. There are in total 4 types of products considered in the dataset:
"ACI": ;
"DB": ;
"SCI": ;
"Annuities": Note that this product contains a lot of missing values.
Age: Numeric. The claim age x associated with the observation, ranging between 18-100.
Year: Numeric. The claim year t associated with the observation, spanning years 2016-2020.
Exposure: Numeric. The central exposure to risk, E_x^c, associated with the observation.
Claim: Numeric. The number of claims ("deaths") associated with the observation.
ExpClaim: Numeric. The expected number of claims associated with the observation.
Qx: Numeric. The crude mortality rate associated with the observation. It can be computed as \frac{\text{Claim}}{\text{Exposure}}.
ExpQx: Numeric. The expected crude mortality rate associated with the observation. It can be computed as \frac{\text{ExpClaim}}{\text{Exposure}}.
StdQx: Numeric. The standard deviation of the crude mortality rate associated with the observation. It can be computed as \sqrt{\frac{\text{Qx} (1-\text{Qx})}{\text{Exposure}}}.

Examples

data("data_summarised")
str(data_summarised)
head(data_summarised)

#extracting a subset of the data (3 products)
data_summarised[data_summarised$Product==c("ACI","DB","SCI"),]

#extracting a subset of the data (ages 35-65)
data_summarised[(data_summarised$Age>=35 & data_summarised$Age<=65),]

BayesMoFo documentation built on Aug. 11, 2025, 1:07 a.m.