statistical remedy needed
hi: the paired t-test is used when you want to reduce variance ( by
differencing the
same observational unit ) or reduce the amount of confounding. in this
case, I think it's more appropriate to use a regular t-test on two
populations. that will also get rid of the autocorrelation problem. of
course, if the variances of the 2 series differs greatly,
then you have a new problem ( and should use welch t-test).
mark
On Fri, Jul 8, 2011 at 6:23 AM, tonyp <petrovaa at gmail.com> wrote:
Hi, I am trying to test for differences in means between two return (time) series. However, the Ljung-Box test is significant due to the long-memory structure of the series ie. autocorrelation is present. I tried to difference twice which is standard (didn't want to overdifference) and still I have, as expected, series correlation. Is there any function in R or a technique some of you guys can suggest me to filter the autocorrelation in order to apply my test? t.test(ts1, ts2 ,alternative='greater', paired=TRUE,var.equal=FALSE, conf.level=0.95) I would totally appreciate if any of you quant minds outthere has done work on that. Thank you in advance. Best, TP -- View this message in context: http://r.789695.n4.nabble.com/statistical-remedy-needed-tp3653641p3653641.html Sent from the Rmetrics mailing list archive at Nabble.com.
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