% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{loans_by_risk.int}
\alias{loans_by_risk.int}
\title{Lending Club Loans by Risk Level}
\format{
A symbolic data frame (\code{symbolic_tbl}) with 35 observations
and 5 variables:
\itemize{
    \item \code{log_income}: Interval-valued log annual income.
    \item \code{interest_rate}: Interval-valued interest rate (\%).
    \item \code{open_accounts}: Interval-valued number of open credit accounts.
    \item \code{total_accounts}: Interval-valued total number of credit accounts.
    \item \code{risk_level}: Risk grade factor (A, B, C, D, E, F, G).
}
Row names are A1--A5, B1--B5, ..., G1--G5.
}
\source{
MAINT.Data R package (\code{LoansbyRisk_minmax} dataset).
}
\usage{
data(loans_by_risk.int)
}
\description{
Interval-valued dataset of 35 Lending Club loan groups classified by
risk level (A through G, 5 groups each). Each group is described by
4 interval-valued financial variables.
}
\section{Metadata}{

\tabular{ll}{
  \strong{Sample size (n)} \tab 35 \cr
  \strong{Variables (p)} \tab 5 \cr
  \strong{Subject area} \tab Finance \cr
  \strong{Symbolic format} \tab Interval \cr
  \strong{Analytical tasks} \tab Classification, Clustering
}
}

\examples{
data(loans_by_risk.int)
}
\references{
Brito, P. and Duarte Silva, A.P. (2012). Modelling interval data with
Normal and Skew-Normal distributions. \emph{Journal of Applied Statistics},
39(1), 3--20.

Original data from the MAINT.Data R package.
}
\keyword{datasets}
\keyword{finance}
\keyword{interval}
