Randomization-based inference in Python
resample Randomisation-based inference in Python based on data resampling and permutation. Features Bootstrap samples (ordinary or balanced with optional stratification) from N-D arrays Apply parametric bootstrap (Gaussian, Poisson, gamma, etc.) on samples Compute bootstrap confidence intervals (percentile or BCa) for any estimator Jackknife estimates of bias and variance of any estimator Permutation-based variants of traditional statistical tests (t-test, K-S test, etc.) Tools for working with empirical distributions (CDF, quantile, etc.) Dependencies Installation requires only numpy and scipy. Installation The latest […]
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