FT_FREQSTATISTICS computes significance probabilities and/or critical
 values of a parametric statistical test or a non-parametric permutation

 Use as
   [stat] = ft_freqstatistics(cfg, freq1, freq2, ...)
 where the input data is the result from FT_FREQANALYSIS, FT_FREQDESCRIPTIVES

 The configuration can contain the following options for data selection
   cfg.channel     = Nx1 cell-array with selection of channels (default = 'all'),
                     see FT_CHANNELSELECTION for details
   cfg.latency     = [begin end] in seconds or 'all' (default = 'all')
   cfg.frequency   = [begin end], can be 'all'       (default = 'all')
   cfg.avgoverchan = 'yes' or 'no'                   (default = 'no')
   cfg.avgovertime = 'yes' or 'no'                   (default = 'no')
   cfg.avgoverfreq = 'yes' or 'no'                   (default = 'no')
   cfg.parameter   = string                          (default = 'powspctrm')

 If you specify cfg.correctm='cluster', then the following is required
   cfg.neighbours  = neighbourhood structure, see FT_PREPARE_NEIGHBOURS

 Furthermore, the configuration should contain
   cfg.method       = different methods for calculating the significance probability and/or critical value
                    'montecarlo'    get Monte-Carlo estimates of the significance probabilities and/or critical values from the permutation distribution,
                    'analytic'      get significance probabilities and/or critical values from the analytic reference distribution (typically, the sampling distribution under the null hypothesis),
                    'stats'         use a parametric test from the MATLAB statistics toolbox,
                    'crossvalidate' use crossvalidation to compute predictive performance

   cfg.design       = Nxnumobservations: design matrix (for examples/advice, please see the Fieldtrip wiki,
                      especially cluster-permutation tutorial and the 'walkthrough' design-matrix section)

 The other cfg options depend on the method that you select. You
 should read the help of the respective subfunction FT_STATISTICS_XXX
 for the corresponding configuration options and for a detailed
 explanation of each method.

 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.