by Patrick Burns.
Abstract: The Ljung-Box test is known to be robust. This paper reports on simulations that show just how robust it is in finite samples. Even so, we demonstrate some practical applications where the robustness of the test fails dramatically. The Ljung-Box test on the ranks of the data provides a suitably robust alternative when the distribution is extremely long-tailed. In particular, the rank Ljung-Box test is highly recommended over the Ljung-Box test for evaluating the adequacy of GARCH models. Simulations also explore properties of the test when applied to binary data. There is some evidence that the test starts to deteriorate as the number of lags exceeds 5% of the length of the series whether or not the data are long-tailed.
jun 25, 26
I’d like to do a song of great social and political import. The code that created the illustrations in Tao Te Programming is now available as the TaoTeProgramming package on [...]
jun 25, 26
Another of the all ye entering here. Issue When subscripting an xts object, columns that don’t exist in the object are silently ignored. Example First, create an xts object: xtx [...]
jun 25, 26
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