title: R time series modeling on weekly data using ts() object
body: <p>I am trying to do time series modeling and forecasting using R based on weekly data like below:</p>
  
  <pre><code>biz week     Amount        Count
  2006-12-27   973710.7     816570
  2007-01-03  4503493.2    3223259
  2007-01-10  2593355.9    1659136
  2007-01-17  2897670.9    2127792
  2007-01-24  3590427.5    2919482
  2007-01-31  3761025.7    2981363
  2007-02-07  3550213.1    2773988
  2007-02-14  3978005.1    3219907
  2007-02-21  4020536.0    3027837
  2007-02-28  4038007.9    3191570
  2007-03-07  3504142.2    2816720
  2007-03-14  3427323.1    2703761
  ...
  2014-02-26  99999999.9   1234567
  </code></pre>
  
  <p>About my data: As seen above, each week is labeled by first day for the week (my week starts on Wed. and ends on Tues). 
  When I construct my <code>ts</code> object, I tried </p>
  
  <pre><code>ts &lt;- ts(df, frequency=52, start=c(2007,1))
  </code></pre>
  
  <p>the problem I have is: </p>
  
  <p>1) Some year may have 53 weeks, so <code>frequency=52</code> will not work for those years;</p>
  
  <p>2) My starting week/date is 2006-12-27, how should I set the start parameter? <code>start=c(2006,52)</code> or <code>start=c(2007,1)</code> since week of 2006-12-27 really cross the year boundary? Also, for modeling, is it better to have complete year worth of data (say for 2007 my start year if I only have partial year worth of data), is it better not to use 2007, instead to start with 2008? What about 2014: since it is not a complete year yet, should I use what I have for modeling or not? Either way, I still have an issue with whether or not to include those weeks in the year boundary like 2006-12-27. Should I include it as <code>wk 1</code> for 2007 or the last week of 2006? </p>
  
  <p>3) When I use <code>ts &lt;- ts(df, frequency=52, start=c(2007,1))</code> and then print it, I got the results shown below, so instead of 2007.01, 2007.02, 2007.52..., I got 2007.000, 2007.019, ..., which it gets from <code>1/52=0.019</code>. This is mathematically correct but not really easy to interpret. Is there a way to label it as the date itself just like a data frame or at least <code>2007 wk1, 2007 wk2...</code></p>
  
  <p>=========</p>
  
  <pre><code>Time Series:
  Start = c(2007, 1) 
  End = c(2014, 11) 
  Frequency = 52 
            Amount        Count
  2007.000   645575.4     493717
  2007.019  2185193.2    1659577
  2007.038  1016711.8     860777
  2007.058  1894056.4    1450101
  2007.077  2317517.6    1757219
  2007.096  2522955.8    1794512
  2007.115  2266107.3    1723002 
  </code></pre>
  
  <p>4) My goal is to model this weekly data and then try to decompose it to see seasonal components. It seems like I have to use the <code>ts()</code> function to convert to a <code>ts</code> object sp that I can use the <code>decompose()</code> function. I tried <code>xts()</code> and I got an error stating <code>" time series has no or less than 2 periods"</code>. I guess this is because <code>xts()</code> won't let me specify the frequency, right? </p>
  
  <pre><code>xts &lt;- xts(df,order.by=businessWeekDate)
  </code></pre>
  
  <p>5) I looked for the answer in this forum and other places as well; most of the examples are monthly, and though there are some weekly time series questions, none of the answers are straightforward. Hopefully somebody can help answer my questions here.</p>