Create rich and fully interactive timeline visualizations.
    Timelines can be included in Shiny apps or R markdown documents.
    'timevis' includes an extensive API to manipulate a timeline after creation,
    and supports getting data out of the visualization into R. Based on the
    'vis.js' Timeline JavaScript library.

Unleash the power of time-series data visualization with ease using our package. Designed with simplicity 
 in mind, it offers three key features through the 'shiny' package output. The first tab shows time- series 
 charts with forecasts, allowing users to visualize trends and changes effortlessly. The second one displays 
 Averages per country presented in tables with accompanying sparklines, providing a quick and attractive 
 overview of the data. The last tab presents A customizable world map colored based on user-defined 
 variables for any chosen number of countries, offering an advanced visual approach to understanding 
 geographical data distributions. This package operates with just a few simple arguments, enabling users 
 to conduct sophisticated analyses without the need for complex programming skills. Transform your 
 time-series data analysis experience with our user-friendly tool.

Estimates time varying regression effects under Cox type models in
    survival data using classification and regression tree. The codes in this package were 
    originally written in S-Plus for the paper "Survival Analysis with Time-Varying Regression
    Effects Using a Tree-Based Approach," by Xu, R. and Adak, S. (2002) <doi:10.1111/j.0006-341X.2002.00305.x>, Biometrics, 58: 305-315.
    Development of this package was supported by NIH grants AG053983 and AG057707,
    and by the UCSD Altman Translational Research Institute, NIH grant UL1TR001442.
    The content is solely the responsibility of the authors and does not necessarily
    represent the official views of the NIH.
    The example data are from the Honolulu Heart Program/Honolulu Asia Aging Study (HHP/HAAS).