Hi,
I ran an experiment with 3 factors, 2 levels and 200 replications and as I want
to test for residuals independence, I used Durbin-Watson in R.
I found two functions (durbin.watson and dwtest) and while both are giving the
same rho, the p-values are greatly differ:
> durbin.watson(mod1)
lag Autocorrelation D-W Statistic p-value
1 -0.04431012 2.088610 0.012
Alternative hypothesis: rho != 0
> dwtest(mod1)
Durbin-Watson test
data: mod1
DW = 2.0886, p-value = 0.9964
alternative hypothesis: true autocorrelation is greater than 0
durbin.watson suggests that I should reject the null hypothesis while dwtest
suggests that I should NOT reject Ho.
If I look it up in the following table:
http://www.stanford.edu/~clint/bench/dw05d.htm, T = 1600 and K = 8 gives dL =
1.90902 and dU = 1.92659.
Which means I should not reject Ho as DW > dU.
Is there a bug in durbin.watson? should I use dwtest instead? can somebody help
me explain what is happening?
Thank you,
~ Hardi
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