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Module: tfp.experimental.substrates.numpy.stats

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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.

cholesky_covariance(...): Cholesky factor of the covariance matrix of vector-variate random samples.

correlation(...): Sample correlation (Pearson) between observations indexed by event_axis.

covariance(...): Sample covariance between observations indexed by event_axis.

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.

stddev(...): Estimate standard deviation using samples.

variance(...): Estimate variance using samples.