Spike Train Analysis Toolkit Documentation  Spike Train Analysis Toolkit Function Reference  correlated_bootstrap

Spike Train Analysis Toolkit

correlated_bootstrap

 CORRELATED_BOOTSTRAP    Calculate correlated bootstrap samples of P(X(t))

 usage 1:     [X] = correlated_bootstrap(X_t);
              [X] = correlated_bootstrap(X_t, N);
 usage 2:     [X] = correlated_bootstrap(X_t, N, spike_rate);

 Inputs:     X_t  -  [N_mc x T] matrix of N_mc samples from a
                     distribution P(X(t) where X_t(:,i) are N_mc
                     samples from time i.

               N  -  number of desired samples [default = 199]

       spike_rate -  [1xT] vector spike rates. [optional] 
        
 Outputs:      X  -  [1xN] samples from distribution P(X). Calculate
                     confidence intervals using PRCTILE.

 Compute N samples from distribution P(X) when all is known is
 N_mc samples from P(X(t)) for each moment in time t=[1,T] and
 samples from P(X(t=a)) is correlated with P(X(t=a+b)).

 Usage 1: Standard correlated bootstrap procedure.

 Usage 2: Correlated bootstrap but adjust P(X(t)) according to the
          linear relationship with the spike rate. Specifiying the
          spike rate centers the resampled estimates about the
          mean spike rate.

 See also: PRCTILE, BOOTSTRAP_PR

 Original coding - Kennel
 Edited - shlens 2005-09-23
 Edited - shlens 2006-02-14

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