Databases
StackOverflow2013
Postsdbo
POApply ksmooth to time series
 

Note that there are some explanatory texts on larger screens.

plurals
  1. POApply ksmooth to time series
    primarykey
    data
    text
    <p>I have the following problem:</p> <p>I have a data frame "test" that looks more or less like this:</p> <pre><code>Date return price vol 20100902 0.3 15 8.5 20100902 0.4 17 8.6 20100902 0.6 19 8.7 ..... 20100903 0.2 13 8.2 20100903 0.4 17 8.6 20100903 0.8 21 9.0 ..... </code></pre> <p>So I have given values for each date (10 per day). What I would like to do now is apply ksmooth() on each date, so e.g. ksmooth(return, price, n.points = 50) for each date. This should give me 50 observations for each date. In addition, I would like a time stamp for the interpolated values. So the resulting frame should like </p> <pre><code>Date return price 20100620 0.3 15 20100620 0.31 15.2 20100620 0.32 15.3 20100620 0.4 17 20100620 0.6 19 ..... 20100621 0.2 13 20100621 0.21 13.1 20100621 0.22 13.2 20100621 0.4 17 20100621 0.8 21 etc. </code></pre> <p>with 50 observations per day. So here is what I'm looking for: take the first 10 observations (e.g. date 1 = 20102006, interpolate and put a time stamp on the interpolated values (20100620). Then, take second 10 observations (date = 20100621), interpolate and put a time stamp on the interpolated values (20100621) and so on.</p> <p>I'm quite new to R, but this is what I tried. I thought of using the zoo() function to that. Before implementing anything, I wanted to make my date entries unique, so I just added hours to each entry</p> <pre><code>test &lt;- read.zoo("test.txt", format = "%Y%m%d") test &lt;- zoo(test, as.POSIXct(time(test)) + 1:26) </code></pre> <p>There probably is something wrong with that, because R complained. Then I thought of using the rollapply() function.</p> <pre><code>roll.test &lt;- rollapply(test, 10, FUN = function(x,y) ksmooth(test$return, + test$price, "normal", bandwidth = 20, n.points = 50) ) </code></pre> <p>Unfortunately the result is very confusing. And the by.column = FALSE demand does not work.</p> <p>I would very appreciate some help. It does not have to build upon my "trial version" at all. Thank you very much Dani</p> <p>My data looks like this:</p> <pre><code>"date" "days" "return" "price" "66" 20100620 91 0.18 1389.373 "67" 20100620 91 0.19 1370.57 "68" 20100620 91 0.19 1353.122 "69" 20100620 91 0.19 1336.291 "70" 20100620 91 0.20 1319.774 "71" 20100620 91 0.20 1303.341 "72" 20100620 91 0.21 1286.656 "326" 20100621 91 0.18 1386.28 "327" 20100621 91 0.18 1367.694 "328" 20100621 91 0.19 1350.375 "329" 20100621 91 0.19 1333.615 "330" 20100621 91 0.20 1317.164 "331" 20100621 91 0.20 1300.783 "332" 20100621 91 0.21 1284.113 </code></pre>
    singulars
    1. PO
      singulars
      1. PTAnswer
    1. This table or related slice is empty.
    1. PTQuestion
    1. USDani
    1. USDani
    plurals
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. PO
      singulars
      1. PTAnswer
    1. VO
      singulars
      1. POApply ksmooth to time series
      1. This table or related slice is empty.
      1. VTUpMod
    2. VO
      singulars
      1. POApply ksmooth to time series
      1. This table or related slice is empty.
      1. VTUpMod
    3. VO
      singulars
      1. POApply ksmooth to time series
      1. USRam Ahluwalia
      1. VTFavorite
    1. COit's always a good idea to provide a toy dataset to test the code. As we don't have test.txt, it's difficult to say why R is complaining.
      singulars
      1. POApply ksmooth to time series
      1. USJoris Meys
    2. COyou could check the function `dput()`. If you give that output, we just can copy-paste it in R and have exactly the same object. Or alternatively, do as I did in my solution to make sure we just have to copy the code and have the object.
      singulars
      1. POApply ksmooth to time series
      1. USJoris Meys
 

Querying!

 
Guidance
A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

SQuiL has stopped working due to an internal error.

If you are curious you may find further information in the browser console, which is accessible through the devtools (F12).

Reload