Spike Train Analysis Toolkit Documentation  Spike Train Analysis Toolkit Function Reference  ctwmcmctree

Spike Train Analysis Toolkit

ctwmcmctree

CTWMCMCTREE Build full CTW tree graph(s) from data.
   Y = CTWMCMCTREE(X,OPTS) returns a cell array or structure Y, depending
   on OPTS, that contains the context-tree weighted tree graph(s) derived
   from the input data in X. X is a single element cell array, like that
   obtained with DIRECTBIN, whose rows represent stimulus repeats and
   whose columns represent time bins, that is a matrix of binned spike
   trains. Y contains a single tree graph, from which one may derive
   "signal" entropy (see CTWMCMCSAMPLE), when X contains a single binned
   spike train. Y contains multiple tree graphs, from which one may derive
   "noise" entropy (see CTWMCMCSAMPLE), when X contains multiple binned
   spike trains.

   The options and parameters for this function are:
      OPTS.beta: Krischevsky-Trofimov ballast parameter used in the
         calculation of local codelength, Le, which also serves as the
         Dirichlet prior parameter in subsequent Markov chain Monte Carlo
         (MCMC) tree sampling. Its value should be greater than 0. The
         default is 1/A, where A is the largest value in the input data X
         plus one.
      OPTS.gamma: The weighting between tree node and its children, used
         when calculating the weighted codelength, Lw. Its value should
         lie between 0 and 1, non-inclusive. The default is 0.5.
      OPTS.max_tree_depth: The maximum tree depth (may be used to conserve
         memory). Its value must be greater than 0. The default is 100000.
      OPTS.h_zero: Flag to indicate use of the H_zero estimator for
         deterministic nodes, that is such nodes will not be weighted when
         true. Note that this value is not used in tree building, per say,
         but in subsequent MCMC sampling. The default is 1 (true).
      OPTS.tree_format: The format for the output tree graph(s). Its value
         may be the string 'cell' or 'struct', which is a trade-off
         between memory consumption and clarity. Data output in cell
         format (the default) consume less memory, but are not easy to
         decipher, whereas data output in struct format are memory-
         intensive, but readily human-readable.
      OPTS.memory_expansion: The ratio by which tree memory is expanded
         when reallocation become necessary during tree building. Its
         value must be greater than or equal to 1. The default is 1.61.

   Y = CTWMCMCTREE(X) uses the default options and parameters.

   [Y,OPTS_USED] = CTWMCMCTREE(X) or [Y,OPTS_USED] = CTWMCMCTREE(X,OPTS)
   additionally return the options used.

   See also DIRECTBIN, CTWMCMC, CTWMCMCSAMPLE, CTWMCMCINFO.

Cross-reference information

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