What actually is Exponentially Weighted Average

[jonaslalin]

Hi @ajaykumar3456,

You are right,

@ajaykumar3456

it is predicting the current value based on the average of the last values using the formulae mentioned vt=0.8vt-1 +0.1*theta_t

It is a technique to smooth out your values, i.e., it is an average. It is an exponentially weighted average in this case since the effect of previous values on the current value declines exponentially.

Now, it is good that I completed your bias correction implementation in your last post
Bias Correction Implementation

On Andrew’s slides, the red line uses bias correction.

Back to your example:

@jonaslalin

temperatures: [25 28 26 22 19 23 27]
v: [ 2.5        5.05       7.145      8.6305     9.66745   11.000705
 12.6006345]
v_corrected: [25.         26.57894737 26.36531365 25.09595813 23.60736002 23.47773706
 24.15288408]

Check out the green line, which is a smooth version of the blue line (temperature). You can see that it doesn’t have the same variance (lower highs and higher lows).

If you use even more values, you will see that bias correction is not that important after a while since it catches up. The orange line will catch up with the green line with more data.