Income2

A sample of 200 observations of full time employees from a municipality
 in Northern Italy who have declared extra income from investment
 sources. The variables are as follows.
 The goal is the possibility in predicting income level based on
 the individual's personal information.

datasets

Provides interface to the 'MATLAB' toolbox 'Flexible Statistical Data Analysis
(FSDA)' which is comprehensive and computationally efficient
software package for robust statistics in regression, multivariate
and categorical data analysis. The current R version implements tools
for regression: (forward search, S- and MM-estimation, least trimmed
squares (LTS) and least median of squares (LMS)), for multivariate analysis
(forward search, S- and MM-estimation), for cluster analysis and cluster-wise regression.
The distinctive feature of our package is the possibility of
monitoring the statistics of interest as a function of breakdown point,
efficiency or subset size, depending on the estimator. This is
accompanied by a rich set of graphical features, such as dynamic
brushing, linking, particularly useful for exploratory data analysis.

Valentin Todorov

fsdaR

Robust Data Analysis Through Monitoring and Dynamic
Visualization

Emmanuele Sordini

Aldo Corbellini

Francesca Torti

Marco Riani

Domenico Perrotta

Andrea Cerioli

Income2 function

A data frame with 200 rows and 6 variables.
The variables are as follows:
<ul>
<li>Age: Age of the person (the minimum is 19 and the maximum is 73).</li>
<li>Education: Number of years of education (the minimum value of 5 is
 primary school, and the maximum value is 16 bachelor degree)</li>
<li>Gender: A factor - Male or Female</li>
<li>ExtraGain: Income from investment sources (profit-losses)
 apart from wages/salary</li>
<li>Hours: total number of declared hours worked during the week.
 The minimum value is 35 and the maximum is 99</li>
<li>Income: total yearly income (Euro amount)</li>
</ul>

Format

Income2 — Income2

Income2: Income2

Description

Usage

Arguments

Format

Examples