1) A small p-value is evidence that there is dependence. So you want to see large p-values. But a large p-value is not really evidence of independence -- merely a lack of evidence of dependence.
You might be able to get a hint of the power of your test (which is what you really care about) from the working paper about Ljung-Box on the Burns Statistics website.
2) The statistic is really an average of the lags up to the stated lag. So if the dependence is all at lag 5, tests with lags below 5 have no power, the lag 5 test has maximum power, and the power decreases as the lag of the test increases above 5.
Patrick Burns
Burns Statistics [EMAIL PROTECTED] +44 (0)20 8525 0696 http://www.burns-stat.com (home of S Poetry and "A Guide for the Unwilling S User")
Aroon Nataraj wrote:
Hi all
I'm using the Box-Ljung test (from within R) to test if a time-series in independently distributed.
2 questions:
1) p-value returned by Box-Ljung:
IF I want to test if the time-series is independant at say 0.05 sig-level (it means that prob of erroneously accepting that the time-series is independent is 0.05 right?)
--> then do I consider time-series as "independant" when
--> p-value (from Box-Ljung) > 0.05
OR
--> p-value < 0.05
Or should i be using (0.95) instead of (0.05) for this case. I'm confused about this (this is a goodness-of-fit test?).
2) Box-Ljung takes a lag argument, say lag=k. Does it check "all lags upto k" OR Does it check "only AT k" (i.e acf val is small at only k?)
thank you in advance. I apologize if the questions are very basic.
Aroon
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