I was reading about Kalman filter. http://web.mit.edu/kirtley/kirtley/binlustuff/literature/control/Kalman%20filter.pdf
They talk about additive noise and error. I need to understand difference between noise, error and residuals.
Did some research like-
https://www.researchgate.net/post/Whats_the_difference_between_noise_and_error_in_a_dataset2 and other answers on Stackexchange like-
What is the difference between errors and residuals?
Can someone please explain me these 3 by talking regression or ARMA model as example?