View source on GitHub
|
Statistical functions.
Functions
assign_log_moving_mean_exp(...): Compute the log of the exponentially weighted moving mean of the exp.
assign_moving_mean_variance(...): Compute one update to the exponentially weighted moving mean and variance.
auto_correlation(...): Auto correlation along one axis.
brier_decomposition(...): Decompose the Brier score into uncertainty, resolution, and reliability.
brier_score(...): Compute Brier score for a probabilistic prediction.
cholesky_covariance(...): Cholesky factor of the covariance matrix of vector-variate random samples.
correlation(...): Sample correlation (Pearson) between observations indexed by event_axis.
count_integers(...): Counts the number of occurrences of each value in an integer array arr.
covariance(...): Sample covariance between observations indexed by event_axis.
cumulative_variance(...): Cumulative estimates of variance.
expected_calibration_error(...): Compute the Expected Calibration Error (ECE).
expected_calibration_error_quantiles(...): Expected calibration error via quantiles(exp(pred_log_prob),num_buckets).
find_bins(...): Bin values into discrete intervals.
histogram(...): Count how often x falls in intervals defined by edges.
kendalls_tau(...): Computes Kendall's Tau for two ordered lists.
log_average_probs(...): Computes log(average(to_probs(logits))) in a numerically stable manner.
log_loomean_exp(...): Computes the log-leave-one-out-mean of exp(logx).
log_loosum_exp(...): Computes the log-leave-one-out-sum of exp(logx).
log_soomean_exp(...): Computes the log-swap-one-out-mean of exp(logx).
log_soosum_exp(...): Computes the log-swap-one-out-sum of exp(logx).
moving_mean_variance_zero_debiased(...): Compute zero debiased versions of moving_mean and moving_variance.
percentile(...): Compute the q-th percentile(s) of x.
quantile_auc(...): Calculate ranking stats AUROC and AUPRC.
quantiles(...): Compute quantiles of x along axis.
stddev(...): Estimate standard deviation using samples.
variance(...): Estimate variance using samples.
windowed_mean(...): Windowed estimates of mean.
windowed_variance(...): Windowed estimates of variance.