I fit a simple linear model y = bX to a data set today, and that produced 24 residuals (I have 24 data points, one for each year from 1984-2007). I would like to test the time-independence of the residuals of my model, and I was recommended by my supervisor to use the Ljung-Box test. The Box.test function in R takes 4 arguments:
x a numeric vector or univariate time series. lag the statistic will be based on lag autocorrelation coefficients. type test to be performed: partial matching is used. fitdf number of degrees of freedom to be subtracted if x is a series of residuals. Unfortunately, I never took a statistics class where I learned the Ljung-Box test, and information about it online is hard to find. What does "lag" mean, and what value would you guys recommend I use for the test? Also, what does "fitdf" represent, and what would the value for that parameter be in my case? Finally, the value of x is a vector of my 24 residuals, correct? Thank you all so much. I apologize for the basic nature of the question. Steven [[alternative HTML version deleted]]
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