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# scipy.special.nctdtr

`scipy.special.``nctdtr`(df, nc, t) = <ufunc 'nctdtr'>

  Cumulative distribution function of the non-central t distribution.

  Parameters: | df : array_like Degrees of freedom of the distribution. Should be in range (0, inf). nc : array_like Noncentrality parameter. Should be in range (-1e6, 1e6). t : array_like Quantiles, i.e. the upper limit of integration.
  Returns: | cdf : float or ndarray The calculated CDF. If all inputs are scalar, the return will be a float. Otherwise it will be an array.

  See also

  `nctdtrit`
    Inverse CDF (iCDF) of the non-central t distribution.
  `nctdtridf`
    Calculate degrees of freedom, given CDF and iCDF values.
  `nctdtrinc`
    Calculate non-centrality parameter, given CDF iCDF values.

  Examples

      >>> from scipy import special
      >>> from scipy import stats
      >>> import matplotlib.pyplot as plt

  Plot the CDF of the non-central t distribution, for nc=0. Compare with the t-distribution from scipy.stats:

      >>> x = np.linspace(-5, 5, num=500)
      >>> df = 3
      >>> nct_stats = stats.t.cdf(x, df)
      >>> nct_special = special.nctdtr(df, 0, x)

      >>> fig = plt.figure()
      >>> ax = fig.add_subplot(111)
      >>> ax.plot(x, nct_stats, 'b-', lw=3)
      >>> ax.plot(x, nct_special, 'r-')
      >>> plt.show()

  (Source code)