[h, p] = btest(X, Y) [h, p] = btest(X, Y, Name, Value)
B-test is a fast maximum mean discrepancy (MMD) kernel two-sample tests that has low sample complexity and is consistent. The B-test uses a smaller than quadratic number of kernel evaluations and avoids completely the computational burden of complex null-hypothesis approximation, while maintaining consistency and probabilistically conservative thresholds on Type I error.
[h, p] = btest(____)
Returns a test decision for the null hypothesis that the data X comes from the same distribution as the data Y. By default B-test computes RBF-kernel for input data points X and Y. However, any kernel might be provided. p corresponds to p-value of the test.
btest allows to specify
- 'Kernel' - kernel function handler, which takes two arguments and returns kernel value for them. Gaussian kernel (default)
- 'Alpha' - Significance level. 0.05 (default) | scalar value in the range (0,1)
- 'BlockSize' - Block size used in B-test. square root of number of samples (default)
More on it under url.