What is it about?
There are many tests for autocorrelation, we want to know which test is more powerful. We use Monte Carlo methods to compare the power of five most commonly used tests for autocorrlation, namely Durbin-Watson, Breusch-Godfrey, Box–Pierce, Ljung Box, and Runs tests in two different linear regression models.
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This page is a summary of: Power Comparisons of Five Most Commonly Used Autocorrelation Tests, Pakistan Journal of Statistics and Operation Research, March 2020, Pakistan Journal of Statistics and Operation Researach,
DOI: 10.18187/pjsor.v16i1.2691.
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