vis.speed.fit

  FIT - Fit two-dimensional Gaussian function to a speed tuning data set.

    [P, SSE, R_SQUARED] = vis.speed.fit(SF, TF, R, MIN_XI, MAX_XI, ...)

    Fits a Gaussian to a set of responses generated by a speed tuning curve
    using a robust multi-start optimization routine to find the best-fit
    parameters.

    Inputs:
      SF      - An array of spatial frequency values.
      TF      - An array of temporal frequency values.
      R       - An array of measured responses.
      MIN_XI  - The lower limit for the speed index ('xi') parameter. (Default: 0)
      MAX_XI  - The upper limit for the speed index ('xi') parameter. (Default: 1)

    Name-Value Pair Arguments:
      numberStartPoints  - The number of initial starting points to try. (Default: 40)
      SpecificStartPoint - A 7xN matrix specifying specific starting
                           points to include in the search.

    Outputs:
      P         - A 7x1 vector with the best-fit parameters.
      SSE       - The total sum of squared errors for the best fit.
      R_SQUARED - The R-squared value (coefficient of determination).

    Parameters (P):
      [A, zeta, xi, sigma_sf, sigma_tf, sf0, tf0]

    See also: vis.speed.fit_nospeed, lsqcurvefit