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POApply / Plyr like functionality without without performance impact in Rollapply or apply.rolling
 

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  1. POApply / Plyr like functionality without without performance impact in Rollapply or apply.rolling
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    <p>I want to use roll apply like functionality on non time series data but computed on a rolling window. So there is no need to convert it into zoo object and back again. Is there a way this can be done on a very large data set?</p> <p><strong>Edit</strong></p> <p>I am using </p> <pre><code>rollapply(zoo(SPYTS[, "Close"]), 2, function(x) x[1] + x[2], fill=0, align="right") </code></pre> <p>on 1 million data points. This takes never seams to stop calculating. Something like </p> <pre><code>SPYTS$LnReturns &lt;- (rbind(0, as.data.frame(log(SPYTS[1:(nrow(SPYTS) - 1), "Close"] / SPYTS[2:nrow(SPYTS), "Close"])))) </code></pre> <p>just takes a few seconds.</p> <p>The function <code>function(x) x[1] + x[2]</code> is just a place holder. The actual function I have in mind is slightly different.</p>
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    1. USSuminda Sirinath S. Dharmasena
    1. USSuminda Sirinath S. Dharmasena
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    1. CO[This](http://stackoverflow.com/q/7225992/324364) question might provide a good starting point.
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    2. COJust so you know, cross-posting like this is generally discouraged. If you choose the "wrong" site, it can be automatically migrated to the appropriate spot. In this case, SO is probably the better choice.
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    3. COI am using `rollapply(zoo(SPYTS[, "Close"]), 2, function(x) x[1] + x[2], fill=0, align="right")` on 1 million data points. This takes never seams to stop calculating. Something like `SPYTS$LnReturns <- (rbind(0, as.data.frame(log(SPYTS[1:(nrow(SPYTS) - 1), "Close"] / SPYTS[2:nrow(SPYTS), "Close"]))))` just takes a few seconds.
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      1. USSuminda Sirinath S. Dharmasena
 

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