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
The email address patrick@burns-stat.com was out of action for a few hours today. It is back now.
jun 25, 26
Customization in R. Basics Several features benefit from being customizable — either because of personal taste or specifics of the environment. The way R implements this flexibility is through the [...]
jun 25, 26
How to control the limits of data values in R plots. R has multiple graphics engines. Here we will talk about the base graphics and the ggplot2 package. We’ll create [...]