@stdlib/stats-base-snanvariancewd
Calculate the variance of a single-precision floating-point strided array ignoring NaN values and using Welford's algorithm.
Calculate the variance of a single-precision floating-point strided array ignoring NaN values and using Welford's algorithm.
Calculate the variance of a single-precision floating-point strided array ignoring NaN values and using a one-pass algorithm proposed by Youngs and Cramer.
Calculate the standard deviation of a single-precision floating-point strided array.
Calculate the standard deviation of a single-precision floating-point strided array ignoring NaN values and using a one-pass trial mean algorithm.
Calculate the standard deviation of a single-precision floating-point strided array ignoring NaN values and using a two-pass algorithm.
Calculate the standard deviation of a single-precision floating-point strided array ignoring NaN values and using a one-pass textbook algorithm.
Calculate the standard deviation of a single-precision floating-point strided array ignoring NaN values and using Welford's algorithm.
Calculate the standard deviation of a single-precision floating-point strided array ignoring NaN values and using a one-pass algorithm proposed by Youngs and Cramer.
Calculate the variance of a strided array using a two-pass algorithm.
Calculate the variance of a strided array using Welford's algorithm.
Calculate the variance of a strided array using a one-pass algorithm proposed by Youngs and Cramer.
Calculate the variance of a strided array using a one-pass textbook algorithm.
Calculate the variance of a single-precision floating-point strided array ignoring NaN values.
Compute the corrected sample standard deviation over all iterated values.
Compute the unbiased sample variance over all iterated values.
Compute an arithmetic mean and corrected sample standard deviation incrementally.
Compute an arithmetic mean and unbiased sample variance incrementally.
Compute an unbiased sample covariance matrix incrementally.
Compute a moving unbiased sample covariance incrementally.
Compute an unbiased sample covariance incrementally.