Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqdescriptives”.

  FT_FREQDESCRIPTIVES computes descriptive univariate statistics of
  the frequency or time-frequency decomposition of the EEG/MEG signal,
  thus the powerspectrum and its standard error.
  Use as
    [freq] = ft_freqdescriptives(cfg, freq)
    [freq] = ft_freqdescriptives(cfg, freqmvar)
  The data in freq should be organised in a structure as obtained from
  from the FT_FREQANALYSIS or FT_MVARANALYSIS function. The output structure is comparable
  to the input structure and can be used in most functions that require
  a freq input.
  The configuration options are
    cfg.variance      = 'yes' or 'no', estimate standard error in the standard way (default = 'no')
    cfg.jackknife     = 'yes' or 'no', estimate standard error by means of the jack-knife (default = 'no')
    cfg.keeptrials    = 'yes' or 'no', estimate single trial power (useful for fourier data) (default = 'no')       = Nx1 cell-array with selection of channels (default = 'all'),
                        see FT_CHANNELSELECTION for details
    cfg.trials        = 'all' or a selection given as a 1xN vector (default = 'all')
    cfg.frequency     = [fmin fmax] or 'all', to specify a subset of frequencies (default = 'all')
    cfg.latency       = [tmin tmax] or 'all', to specify a subset of latencies (default = 'all')
  A variance estimate can only be computed if results from trials and/or
  tapers have been kept.
  Descriptive statistics of bivariate metrics is not computed by this function anymore. To this end you
  To facilitate data-handling and distributed computing you can use
    cfg.inputfile   =  ...
    cfg.outputfile  =  ...
  If you specify one of these (or both) the input data will be read from a *.mat
  file on disk and/or the output data will be written to a *.mat file. These mat
  files should contain only a single variable, corresponding with the
  input/output structure.