1 Duration Models

1.1 Composition of the portfolio

Analyse the composition of the portfolio: covariates, frequency by covariates.

First, load the training and testing sets, located in the following folder: data/canada_panel/ (CanadaPanelTrain.csv and CanadaPanelTest.csv, respectively).

library(tidyverse)

Define a function that computes summary statistics for a vector of numerics:

Average
Standard deviation
Min and Max
Median
Other percentiles (e.g., 10th, 25th, 75th, and 90th)

Try to account for possible NA values. Name the function my_summary.

#' my_summary
#' Returns a tibble with summary statistics for a numerical vector
#' @param x vector of numerics
my_summary <- function(x) {
  
}

Use the function on a single variable from the training sample:

Apply this function to multiple variables of your choice to explore the dataset and put the results in a table. You may either use a for loop, lapply() or map() (pick the option you are more comfortable with). Do not forget to add the variable name to be able to identify the variables.

Plot the distribution of claims on a barplot. You may display the distribution of gender among each claims levels (by showing the proportion of each gender within the bars). The result may look like the figure displayed below:

Plot a boxplot of exposure time depending on marital status and vehicle use. Use faceting to separate the data according to vehicule use. The resulting plot should look like the one below:

Telematics - Exercises

Insurance Data Science: Use and Value of Unusual Data

August 2019

1 Duration Models

1.1 Composition of the portfolio