@COMMENT This file was generated by bib2html.pl <https://sourceforge.net/projects/bib2html/> version 0.94
@COMMENT written by Patrick Riley <http://sourceforge.net/users/patstg/>
@InProceedings{VAST09-htpc, 
  author =      {Chad A. Steed and J. Edward {Swan~II} and T.J. Jankun-Kelly and 
                 Patrick J. Fitzpatrick}, 
  title =       {Guided Analysis of Hurricane Trends Using Statistical Processes 
                 Integrated with Interactive Parallel Coordinates}, 
  booktitle =   {Proceedings of the IEEE Symposium on Visual 
                 Analytics Science and Technology (VAST 2009)}, 
  year =        2009, 
  location =    {Atlantic City, New Jersey, USA}, 
  date =        {October 12--13}, 
  month =       {October}, 
  pages =       {19--26}, 
  abstract =    { 
This paper demonstrates the promise of augmenting interactive 
multivariate representations with information from statistical processes 
in the domain of weather data analysis. Statistical regression, 
correlation analysis, and descriptive statistical calculations are 
integrated via graphical indicators into an enhanced parallel coordinates 
system, called the Multidimensional Data eXplorer (MDX). 
These statistical indicators, which highlight significant 
associations in the data, are complemented with interactive visual 
analysis capabilities.  The resulting system allows a smooth, interactive, 
and highly visual workflow. 
The system's utility is demonstrated with an extensive hurricane 
climate study that was conducted by a hurricane expert. 
In the study, the expert used a new data set of environmental weather 
data, composed of 28 independent variables, to predict annual 
hurricane activity. MDX shows the Atlantic Meridional 
Mode increases the explained variance of hurricane seasonal activity by 7-15\% 
and removes less significant variables used in earlier studies. 
The findings and feedback from the expert (1) validate the utility of 
the data set for hurricane prediction, and (2) indicate that the 
integration of statistical processes with interactive parallel 
coordinates, as implemented in \appname, 
addresses both deficiencies in traditional weather data analysis and 
exhibits some of the expected benefits of visual data analysis. 
}, 
}