wnba2014

The data set contains information about the season 2014.
 The data can be seen in 'Polygonal data analysis: A new framework in symbolic data analysis' paper.

datasets

A toolbox in symbolic data framework as a statistical learning and data mining solution for symbolic polygonal data analysis. This study is a new approach in data analysis and it was proposed by
Silva et al. (2019) <doi:10.1016/j.knosys.2018.08.009>. The package presents the estimation of main descriptive statistical measures, e.g, mean, covariance, variance, correlation and coefficient of variation.
In addition, a method to obtain polygonal data from classical data is presented. Empirical probability distribution function based on symbolic polygonal histogram and a regression model with its main measures are presented.

Wagner Silva

psda

Polygonal Symbolic Data Analysis

Renata Souza

Francisco Cysneiros

wnba2014 function

A data.frame with 4022 rows and 6 variables:<dl class="dl-horizontal">
 <dt>player_id</dt><dd>Identification of player.</dd>
 <dt>team_pts</dt><dd>Number of points made by team.</dd>
 <dt>opp_pts</dt><dd>Number of points made by opponent.</dd>
 <dt>minutes</dt><dd>Minutes played.</dd>
 <dt>fgatt</dt><dd>Field goal attempts.</dd>
 <dt>efficiency</dt><dd>Efficiency.</dd>
</dl>

Format

Women National Basketball Association 2014 (WNBA 2014). — wnba2014

A data.frame with 4022 rows and 6 variables:<dl class='dl-horizontal'>
 <dt>player_id</dt><dd>Identification of player.</dd>
 <dt>team_pts</dt><dd>Number of points made by team.</dd>
 <dt>opp_pts</dt><dd>Number of points made by opponent.</dd>
 <dt>minutes</dt><dd>Minutes played.</dd>
 <dt>fgatt</dt><dd>Field goal attempts.</dd>
 <dt>efficiency</dt><dd>Efficiency.</dd>
</dl>

wnba2014: Women National Basketball Association 2014 (WNBA 2014).

Description

Usage

Arguments

Format