title: Which R time/date class and package to use?
body: <p>I have a limited time series exposure in R. So, I wonder which time/date class (and associated package) would be most appropriate to start with.</p>
  <p>Among the plethora of packages available at <a href="http://cran.r-project.org/web/views/TimeSeries.html" rel="nofollow noreferrer">CRAN task view</a>, I so far favor the <a href="http://cran.r-project.org/web/packages/timeDate/index.html" rel="nofollow noreferrer"><code>timeDate</code></a>, which is a S4 oriented and has nice support for location dependent particularities such as holidays and daylight saving times.</p>
  <p>The community apparently favors the <a href="http://cran.r-project.org/web/packages/zoo/index.html" rel="nofollow noreferrer"><code>zoo</code></a> package. <a href="http://cran.r-project.org/web/packages/chron/index.html" rel="nofollow noreferrer"><code>chron</code></a> is also popular.<br />
  [edit: Here is a list of time/date implementations which <code>lubridate</code> package refers to:  <strong>POSIXct, POSIXlt, Date, chron, yearmon, yearqtr, zoo, zooreg, timeDate, xts, its, ti, jul, timeSeries,  fts</strong>. Also <code>lubridate</code> itself has  handy time classes <code>duration</code>, <code>period</code> and <code>interval</code>.]</p>
  <p>Would really appreciate if somebody with experience with multiple packages would share his opinion on how the available time/date classes compare in terms of usability and extensibility.</p>
  <p>Some points of interest (in random order):</p>
  <ul>
  <li>internationalization (holidays, timezones etc)</li>
  <li>readily available statistical modeling procedures</li>
  <li>readily available visualization tools</li>
  <li>ease of use</li>
  <li>compatibility with builtin date/time-series classes (POSIX,ts)</li>
  <li>extensibility (S4 is desirable)</li>
  <li>best to use with <a href="http://cran.r-project.org/web/packages/lubridate/" rel="nofollow noreferrer"><code>lubridate</code></a></li>
  </ul>
  <p>Thanks.</p>