CTWMCMCINFO Estimate information from CTW tree based entropy estimates.
Y = CTWMCMCINFO(X,REP_BINNED,OPTS) accepts a structure X containing the
fields 'signal' and 'noise' that hold entropy estimates derived via the
context-tree weighting (CTW) Markov chain Monte Carlo (MCMC) method, as
obtained from CTWMCMCSAMPLE. X is copied to the output Y, and the field
'information' is added that includes an estimate of the mutual
information between the signal and noise, and its confidence interval.
The additional required input REP_BINNED is the binned spike trains
from which 'noise' estimates were derived, as obtained with DIRECTBIN.
The options and parameters for this function are:
OPTS.match_rates: Flag to indicate whether resampled spike trains
should be adjusted based on the original spike rates. The default
is 1 (true).
OPTS.confidence_interval: The confidence interval (in percent). The
default is 95, indicating the 2.5 and 97.5 percentiles.
Y = CTWMCMCINFO(X,REP_BINNED) uses the default options and parameters.
[Y,OPTS_USED] = CTWMCMCINFO(X,REP_BINNED) or [Y,OPTS_USED] =
CTWMCMCINFO(X,REP_BINNED,OPTS) additionally return the options used.
See also DIRECTBIN, CTWMCMC, CTWMCMCSAMPLE.
This function calls: