I try to perform a multiple linear regression on a data set that has multiple measurements for each day over a period of multiple months.
In more detail I have ~3 to 10 observations per day on prices customers paid for a product. I investigate a time span of 3 months.
Now I want to check for autocorrelation and I face two problems:
– There are multiple observations per day and Durbin-Watson test works only if there is only one observation per day. Is it appropriate when I average the prices for each day? The problem then is, that there may be a large variance and the mean may not be sensible.
– There are missing values. So, at some days nowone bought the product. What to do with missing values?
Kind regard and thanks in advance,