MKFstep.fading {NTS} | R Documentation |
One Propagation Step under Mixture Kalman Filter for Fading Channels
Description
This function implements the one propagation step under mixture Kalman filter for fading channels.
Usage
MKFstep.fading(mm, II, mu, SS, logww, yyy, par, xdim, ydim, resample)
Arguments
mm |
the Monte Carlo sample size. |
II |
the indicators. |
mu |
the mean in the last iteration. |
SS |
the covariance matrix of the Kalman filter components in the last iteration. |
logww |
is the log weight of the last iteration. |
yyy |
the observations with |
par |
a list of parameter values. |
xdim |
the dimension of the state variable |
ydim |
the dimension of the observation |
resample |
a binary vector of length |
Value
The function returns a list with components:
xhat |
the fitted value. |
xhatRB |
the fitted value using Rao-Blackwellization. |
Iphat |
the estimated indicators. |
IphatRB |
the estimated indicators using Rao-Blackwellization. |
References
Tsay, R. and Chen, R. (2018). Nonlinear Time Series Analysis. John Wiley & Sons, New Jersey.