Introduction - If you have any usage issues, please Google them yourself
runs Kalman-Bucy filter over observations matrix Z
for 1-step prediction onto matrix X (X can = Z)
with model order p
V = initial covariance of observation sequence noise
returns model parameter estimation sequence A,
sequence of predicted outcomes y_pred
and error matrix Ey (reshaped) for y and Ea for a
along with inovation prob P = P(y_t | D_t-1) = evidence
Packet : 29782201kalman.rar filelist
kalman\gaussres.m
kalman\kf.m
kalman\kfdemo.m
kalman\kfdemo.mat
kalman\normalis.m
kalman\read_me.txt
kalman\waitbar.m
kalman