data_summarised {BayesMoFo} | 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),]