12/31/2020 · Distance computations ( scipy .spatial. distance )¶ Function reference¶ Distance matrix computation from a collection of raw observation vectors stored in a rectangular array. pdist (X[, metric]) Pairwise distances between observations in n.
12/31/2020 · scipy .stats.kstest¶ scipy .stats.kstest (rvs, cdf, args = (), N = 20, alternative = ‘two-sided’, mode = ‘auto’) [source] ¶ Performs the (one sample or two samples) Kolmogorov-Smirnov test for goodness of fit. The one-sample test performs a test of the distribution F(x) of an observed random variable against a given distribution G(x).
12/31/2020 · scipy .stats. ks _2samp¶ scipy .stats. ks _2samp (data1, data2, alternative = ‘two-sided’, mode = ‘auto’) [source] ¶ Compute the Kolmogorov-Smirnov statistic on 2 samples. This is a two-sided test for the null hypothesis that 2 independent samples are drawn from the same continuous distribution.
5/11/2014 · scipy .stats. ks _2samp¶ scipy .stats. ks _2samp(data1, data2) [source] ¶ Computes the Kolmogorov-Smirnov statistic on 2 samples. This is a two-sided test for the null hypothesis that 2 independent samples are drawn from the same continuous distribution.
12/31/2020 · scipy .stats.wasserstein_ distance ¶ scipy .stats.wasserstein_ distance (u_values, v_values, u_weights = None, v_weights = None) [source] ¶ Compute the first Wasserstein distance between two 1D distributions. This distance is also known as the earth mover’s distance , since it can be seen as the minimum amount of “work” required to transform (u).
scipy .stats.kstest — SciPy v1.6.0 Reference Guide, scipy .stats.kstest — SciPy v1.6.0 Reference Guide, The p-values are wrong if the parameters are estimated. However, the test statistic or p-values can still be interpreted as a distance measure. The distribution that describes the data best, is the one with the smallest distance to the ECDF. KS uses a max or sup norm. Anderson-Darling or Von-Mises use weighted squared differences.
10/17/2018 · 2 sample Kolmogorov Smirnov test (KS test) is about finding the maximal vertical distance between two empirical cumulative distributions a large max distance is unlikely under the null assumption that the two empirical distributions are sampled from the same theoretical curve. This is implemented in scipy.stats.ks_twosamp.
3/7/2019 · My issue is about scipy .stats. stats._cdf_ distance and p = np.inf. Mathematically, p = np.inf is the same as the Kolmogorov-Smirnov statistic ( ks _2samp) and should handle it according Reproducing code example: import numpy as np import scipy .stats np.random.seed(1) A = np.random.uniform(size=100000) B = np.random.uniform(size=len(A)-1) # Just to.
7/18/2018 · @CharlesMasson I have used your code to calculate wasserstein distance and energy distance . I am comparing how these distances stack up against ks test for two tags which have different spread. In the picture attached below, I am surpris…
In statistics, the Kolmogorov–Smirnov test (K–S test or KS test) is a nonparametric test of the equality of continuous (or discontinuous, see Section 2.2), one-dimensional probability distributions that can be used to compare a sample with a reference probability distribution (one-sample K–S test), or to compare two samples (two-sample K–S test).
NumPy, Matplotlib, pandas, TensorFlow, Python
