scipy.special.nctdtr#
- scipy.special.nctdtr(df, nc, t, out=None) = <ufunc 'nctdtr'>#
- Cumulative distribution function of the non-central t distribution. - Parameters:
- dfarray_like
- Degrees of freedom of the distribution. Should be in range (0, inf). 
- ncarray_like
- Noncentrality parameter. 
- tarray_like
- Quantiles, i.e., the upper limit of integration. 
- outndarray, optional
- Optional output array for the function results 
 
- Returns:
- cdfscalar or ndarray
- The calculated CDF. If all inputs are scalar, the return will be a float. Otherwise, it will be an array. 
 
 - See also - Notes - This function calculates the CDF of the non-central t distribution using the Boost Math C++ library [1]. - Note that the argument order of - nctdtris different from that of the similar- cdfmethod of- scipy.stats.nct: t is the last parameter of- nctdtrbut the first parameter of- scipy.stats.nct.cdf.- References [1]- The Boost Developers. “Boost C++ Libraries”. https://www.boost.org/. - Examples - >>> import numpy as np >>> 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() 