credit


A random sample of 500 observations of customers applying for personal loans at an Australian bank. All customers were 25 years old or under.


datasets

All data sets required for the examples and exercises in
the book "Forecasting: principles and practice" by Rob J
Hyndman and George Athanasopoulos. All packages required to run
the examples are also loaded.

Rob Hyndman

Data for "Forecasting: principles and practice"

credit function

A data frame with 500 observations on the following 7 variables.
  <dl>
    <dt><code>score</code></dt><dd>a numeric vector giving the credit scores calculated by the bank on a scale from 0 to 100.</dd> <dt><code>savings</code></dt><dd>a numeric vector giving the total personal savings of each customer (in thousands of $).</dd> <dt><code>income</code></dt><dd>a numeric vector giving the total net income of each customer (in thousands of $).</dd> <dt><code>fte</code></dt><dd><code>TRUE</code> if the customer has full time employment, and <code>FALSE</code> otherwise.</dd> <dt><code>single</code></dt><dd><code>TRUE</code> if the customer is single, and <code>FALSE</code> otherwise.</dd> <dt><code>time.address</code></dt><dd>a numeric vector giving the number of months each customer has lived at their current address.</dd> <dt><code>time.employed</code></dt><dd>a numeric vector giving the number of months each customer has been with their current employer.</dd> </dl> 

credit: Credit ratings on personal loans from an Australian bank.

Description

Usage

Arguments

Format

Examples