Hi guys I am trying to writ e a code on python to correct forecast data using Kalman Filter. I am following the equations and recommendations in this link : http://www.swarthmore.edu/NatSci/echeeve1/Ref/Kalman/ScalarKalman.html. At some point, I have written a function which satisfies me since I don't know whatsoever how to use the pykalman module to correct estimations. I am using just one parameter (unidimensional and univariate time series), so my matrices form will be a numerical value. My main problem is what is the transition matrix? In many paper they just use a transition matrix of 1 but I think this is not rigorous since it would mean that: forecast(t) = A * forecast(t-1) We do not have a constant value of forecast so what would be my transition matrix?
Hypothesis 1: Can I just try to see a correlation coefficient between two estimated values then take the mean of those coefficients for my first day of forecast.By the way this transition matrix will be just an initialization and will change for each forecast following