@stdlib/stats-incr-cv
Compute the coefficient of variation (CV) incrementally.
Compute the coefficient of variation (CV) incrementally.
Compute an exponentially weighted standard deviation incrementally.
Compute an exponentially weighted variance incrementally.
Weibull distribution variance.
Calculate the standard deviation of a strided array ignoring NaN values.
Calculate the standard deviation of a strided array ignoring NaN values and using a one-pass trial mean algorithm.
Calculate the standard deviation of a double-precision floating-point strided array ignoring NaN values.
Calculate the standard deviation of a double-precision floating-point strided array ignoring NaN values and using a one-pass trial mean algorithm.
Calculate the standard deviation of a double-precision floating-point strided array ignoring NaN values and using a two-pass algorithm.
Calculate the standard deviation of a double-precision floating-point strided array ignoring NaN values and using a one-pass textbook algorithm.
Calculate the standard deviation of a double-precision floating-point strided array ignoring NaN values and using Welford's algorithm.
Calculate the standard deviation of a double-precision floating-point strided array ignoring NaN values and using a one-pass algorithm proposed by Youngs and Cramer.
Calculate the variance of a double-precision floating-point strided array provided a known mean and using Neely's correction algorithm.
Calculate the variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm.
Rayleigh distribution variance.
Student's t distribution variance.
Calculate the standard deviation of a strided array ignoring NaN values and using a two-pass algorithm.
Calculate the standard deviation of a strided array ignoring NaN values and using a one-pass textbook algorithm.
Calculate the standard deviation of a strided array ignoring NaN values and using Welford's algorithm.
Calculate the standard deviation of a strided array ignoring NaN values and using a one-pass algorithm proposed by Youngs and Cramer.