A common step in preprocessing data for information theory is removing a persistent seasonal signal in the data. To do this usually a day of year average value is subtracted from each data point, but to do this we would need several years of data prior to the year that we are processing. Right now the plan is to analyze 2019. Not sure how much data we'd need to do this effectively.
A common step in preprocessing data for information theory is removing a persistent seasonal signal in the data. To do this usually a day of year average value is subtracted from each data point, but to do this we would need several years of data prior to the year that we are processing. Right now the plan is to analyze 2019. Not sure how much data we'd need to do this effectively.