creditCard

A dataset containing credit history information for credit card applicants. This dataset is sourced from the AER package.

datasets

Stepwise regression is a statistical technique used for model selection. This package streamlines stepwise regression analysis by supporting multiple regression types(linear, Cox, logistic, Poisson, Gamma, and negative binomial), incorporating popular selection strategies(forward, backward, bidirectional, and subset), and offering essential metrics. It enables users to apply multiple selection strategies and metrics in a single function call, visualize variable selection processes, and export results in various formats. StepReg offers a data-splitting option to address potential issues with invalid statistical inference and a randomized forward selection option to avoid overfitting. We validated StepReg's accuracy using public datasets within the SAS software environment. Additionally, StepReg features an interactive Shiny application to enhance usability and accessibility.

Junhui Li

StepReg

Stepwise Regression Analysis

Kai Hu

Xiaohuan Lu

Sushmita N Nayak

Cesar Bautista Sotelo

Michael A Lodato

Wenxin Liu

Lihua Julie Zhu

creditCard function

A data frame with 1,319 observations and 12 variables:<dl>
 <dt>card</dt>
<dd>Factor. Whether the credit card application was accepted (Yes/No)</dd> <dt>reports</dt>
<dd>Numeric. Number of major derogatory reports on the applicant's credit history</dd> <dt>age</dt>
<dd>Numeric. Age in years plus twelfths of a year (e.g., 30.5 represents 30 years and 6 months)</dd> <dt>income</dt>
<dd>Numeric. Annual income in USD (divided by 10,000)</dd> <dt>share</dt>
<dd>Numeric. Ratio of monthly credit card expenditure to yearly income</dd> <dt>expenditure</dt>
<dd>Numeric. Average monthly credit card expenditure in USD</dd> <dt>owner</dt>
<dd>Factor. Home ownership status (Yes/No)</dd> <dt>selfemp</dt>
<dd>Factor. Self-employment status (Yes/No)</dd> <dt>dependents</dt>
<dd>Numeric. Number of dependents</dd> <dt>months</dt>
<dd>Numeric. Number of months living at current address</dd> <dt>majorcards</dt>
<dd>Numeric. Number of major credit cards held</dd> <dt>active</dt>
<dd>Numeric. Number of active credit accounts</dd>
</dl>

Format

Credit Card Application Dataset — creditCard

A data frame with 1,319 observations and 12 variables:<dl>
 <dt>card</dt>
<dd>Factor. Whether the credit card application was accepted (Yes/No)</dd>

 <dt>reports</dt>
<dd>Numeric. Number of major derogatory reports on the applicant's credit history</dd>

 <dt>age</dt>
<dd>Numeric. Age in years plus twelfths of a year (e.g., 30.5 represents 30 years and 6 months)</dd>

 <dt>income</dt>
<dd>Numeric. Annual income in USD (divided by 10,000)</dd>

 <dt>share</dt>
<dd>Numeric. Ratio of monthly credit card expenditure to yearly income</dd>

 <dt>expenditure</dt>
<dd>Numeric. Average monthly credit card expenditure in USD</dd>

 <dt>owner</dt>
<dd>Factor. Home ownership status (Yes/No)</dd>

 <dt>selfemp</dt>
<dd>Factor. Self-employment status (Yes/No)</dd>

 <dt>dependents</dt>
<dd>Numeric. Number of dependents</dd>

 <dt>months</dt>
<dd>Numeric. Number of months living at current address</dd>

 <dt>majorcards</dt>
<dd>Numeric. Number of major credit cards held</dd>

 <dt>active</dt>
<dd>Numeric. Number of active credit accounts</dd>


</dl>

Credit Card Application Dataset

creditCard: Credit Card Application Dataset

Description

Usage

Arguments

Format

Details

See Also

Examples