Stepwise Predictor Selection Method

• Title: Stepwise Predictors Selection Method
• Course: Advanced Mathematical Statistics II, Spring 2018
• Author: Minwoo Bae (minubae.math@gmail.com)
• Institute: The Department of Mathematics, CUNY

Project Description:

Consider the Benzene concentration as response Y variable and others as predictors.
Carry out Stepwise Variable selection method to select an appropriate subset of assumptions.
Use AIC, Adjusted R^2, and C_p plot to select suitable subset of variable.

Data Set Information:

The dataset contains 9358 instances of hourly averaged responses from an array of 5 metal oxide chemical sensors embedded
in an Air Quality Chemical Multisensor Device. The device was located on the field in a significantly polluted area,
at road level,within an Italian city. Data were recorded from March 2004 to February 2005 (one year)representing
the longest freely available recordings of on field deployed air quality chemical sensor devices responses.
Ground Truth hourly averaged concentrations for CO, Non Metanic Hydrocarbons, Benzene, Total Nitrogen Oxides (NOx) and
Nitrogen Dioxide (NO2) and were provided by a co-located reference certified analyzer. Evidences of cross-sensitivities
as well as both concept and sensor drifts are present as described in De Vito et al., Sens. And Act. B, Vol. 129,2,2008
(citation required)eventually affecting sensors concentration estimation capabilities.
Missing values are tagged with -200 value.
This dataset can be used exclusively for research purposes. Commercial purposes are fully excluded.

Data Set Sources: https://archive.ics.uci.edu/ml/datasets/Air+quality