@stdlib/stats-base-nanstdevtk
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 a one-pass textbook algorithm.
Calculate the standard deviation of a strided array ignoring NaN values and using a one-pass algorithm proposed by Youngs and Cramer.
Calculate the median value of a sorted single-precision floating-point strided array.
Calculate the mid-range of a single-precision floating-point strided array.
Calculate the minimum value of a single-precision floating-point strided array.
Calculate the minimum absolute value of a single-precision floating-point strided array.
Calculate the minimum value of a sorted single-precision floating-point strided array.
Calculate the maximum value of a single-precision floating-point strided array according to a mask.
Calculate the maximum absolute value of a single-precision floating-point strided array, ignoring NaN values.
Calculate the range of a single-precision floating-point strided array according to a mask, ignoring NaN values.
Calculate the range of a single-precision floating-point strided array, ignoring NaN values.
Calculate the standard deviation of a single-precision floating-point strided array ignoring NaN values and using Welford's algorithm.
Calculate the arithmetic mean of a strided array, ignoring NaN values and using a two-pass error correction algorithm.
Calculate the minimum value of a strided array via a callback function, ignoring NaN values.
Calculate the minimum absolute value of a strided array, ignoring NaN values.
Calculate the maximum value of a strided array according to a mask, ignoring NaN values.
Calculate the minimum value of a strided array according to a mask, ignoring NaN values.
Calculate the standard deviation of a strided array ignoring NaN values and using Welford's algorithm.
Calculate the variance of a strided array ignoring NaN values.
Calculate the variance of a strided array ignoring NaN values and using a one-pass trial mean algorithm.