Module: tfp.stats

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.