JSPM

A JavaScript extension package for building strong and modern applications.

Calculates the weighted mean of an array of numbers

Chi-squared distribution expected value.

Calculate the arithmetic mean of a strided array using a two-pass error correction algorithm.

Calculate the arithmetic mean of a strided array.

Haraka plugin for the AVG virus scanner

Provides a method to compute a moving arithmetic mean incrementally.

Computes the median of an array.

Poisson distribution expected value.

Beta distribution expected value.

A collection of useful utility functions with associated TypeScript types. All functions have been unit tested.

Student's t distribution expected value.

Binomial distribution expected value.

Normal distribution expected value.

Lognormal distribution expected value.

Computes the median of an array ignoring non-numeric values.

Computes the truncated mean of an array.

Calculate the median value of a sorted strided array.

Compute an arithmetic mean incrementally.

Small math function library

Computes the arithmetic mean.

Average module. An efficient way to calculate average.

Provides a method to compute an arithmetic mean incrementally.

Node-RED added node functions.

Uniform distribution median.

Uniform distribution expected value.

Weibull distribution expected value.

A Node-RED node to calculate average.

This package is a combination of many useful functions.

Exponential distribution expected value.

Compute a moving arithmetic mean incrementally.

efficient rolling stats added one by one with no recalculation

turf average module

Calculate the simple moving average of an array.

Triangular distribution expected value.

F distribution expected value.

Compute an arithmetic mean and corrected sample standard deviation incrementally.

Compute a moving mean error (ME) incrementally.

Compute a geometric mean incrementally.

Compute a moving arithmetic mean and unbiased sample variance incrementally.

Compute the mean absolute percentage error (MAPE) incrementally.

Compute a moving geometric mean incrementally.

Compute an arithmetic mean and unbiased sample variance incrementally.

Compute a moving mean directional accuracy (MDA) incrementally.

Compute the mean absolute error (MAE) incrementally.

Compute an arithmetic mean of absolute values incrementally.

Compute a moving arithmetic mean of absolute values incrementally.

Compute the mean directional accuracy (MDA) incrementally.

Compute a harmonic mean incrementally.

Compute an exponentially weighted mean incrementally.

Compute the arithmetic mean over all iterated values.

Compute a moving mean absolute error (MAE) incrementally.

Compute an arithmetic mean of squared absolute values incrementally.

Compute a moving arctangent mean absolute percentage error (MAAPE) incrementally.

Compute a moving harmonic mean incrementally.

DaHao.de 播放引擎（TypeScript 版）

Compute a moving mean absolute percentage error (MAPE) incrementally.

Compute the mean percentage error (MPE) incrementally.

Compute a weighted arithmetic mean incrementally.

Compute a moving mean percentage error (MPE) incrementally.

Compute a moving arithmetic mean and corrected sample standard deviation incrementally.

Compute a moving arithmetic mean of squared absolute values incrementally.

Calculates various averages of an array

Compute the mean error (ME) incrementally.

Compute the mean arctangent absolute percentage error (MAAPE) incrementally.

Chi distribution expected value.

Gamma distribution expected value.

Arcsine distribution median.

Arcsine distribution expected value.

Calculate the arithmetic mean of a double-precision floating-point strided array using a two-pass error correction algorithm.

Beta prime distribution expected value.

The javascript library for using aggregate functions on array of objects

A simple command-line tool to convert SVG file to AVG (Alexa Presentation Language)

Geometric distribution expected value.

Calculate the mean and variance of a double-precision floating-point strided array using a two-pass algorithm.

Rayleigh distribution expected value.

Bernoulli distribution expected value.

Lévy distribution expected value.

Converts Text to AVG at runtime for easy use with the Alexa Presentation Language

Calculate the arithmetic mean of a double-precision floating-point strided array.

Gumbel distribution mean.

Calculate the mean and standard deviation of a double-precision floating-point strided array.

Raised cosine distribution expected value.

Calculate the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and returning an extended precision result.

Laplace distribution expected value.

slice file or join files or avg slice file.

Erlang distribution expected value.

Fréchet distribution expected value.

Kumaraswamy's double bounded distribution expected value.

Calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values and using ordinary recursive summation with extended accumulation.

total for stream json object

Logistic distribution expected value.

Calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation.

Inverse gamma distribution expected value.

Degenerate distribution expected value.

Pareto (Type I) distribution expected value.

Calculate the mean and standard deviation of a double-precision floating-point strided array using a two-pass algorithm.

Discrete uniform distribution expected value.

avg disable devtool(private)

Create an iterator which iteratively computes a cumulative arithmetic mean of absolute values.

Calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result.

Create an iterator which iteratively computes a cumulative harmonic mean.

Create an iterator which iteratively computes a cumulative geometric mean.

The Javascript library used for aggregate on array of objects

Calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values and using extended accumulation.

Calculate the arithmetic mean of a double-precision floating-point strided array, ignoring NaN values.

Calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and returning an extended precision result.

Calculate the arithmetic mean of a single-precision floating-point strided array using extended accumulation and returning an extended precision result.

Calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values and using a two-pass error correction algorithm.

Calculate the arithmetic mean of a single-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm.

Calculate the arithmetic mean of a strided array using Welford's algorithm.

Create an iterator which iteratively computes a moving arithmetic mean.

Calculate the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm.

Calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values.

Calculate the arithmetic mean of a strided array, ignoring NaN values and using ordinary recursive summation.

Calculate the median value of a sorted double-precision floating-point strided array.

Calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values, using extended accumulation, and returning an extended precision result.

Calculate the arithmetic mean of a single-precision floating-point strided array using an improved Kahan–Babuška algorithm.

Calculate the arithmetic mean of a strided array using a second-order iterative Kahan–Babuška algorithm.

Calculate the arithmetic mean of a double-precision floating-point strided array, ignoring NaN values and using pairwise summation.

Calculate the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation.

Calculate the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation.

Calculate the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm.

Calculate the median value of a sorted single-precision floating-point strided array.

Calculate the arithmetic mean of a strided array using pairwise summation.

Calculate the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result.

Calculate the arithmetic mean of a strided array, ignoring NaN values and using Welford's algorithm.

Calculate the arithmetic mean of a double-precision floating-point strided array, ignoring NaN values and using ordinary recursive summation.

Calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values, using ordinary recursive summation with extended accumulation, and returning an extended precision result.

Calculate the arithmetic mean of a double-precision floating-point strided array using pairwise summation.

Calculate the simple moving average for an array.

Create an iterator which iteratively computes a cumulative arithmetic mean of squared absolute values.

Calculate the arithmetic mean of a strided array, ignoring NaN values.

Calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values and using Welford's algorithm.

Calculate the arithmetic mean of a strided array using an improved Kahan–Babuška algorithm.

Calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm.

Calculate the arithmetic mean of a strided array using ordinary recursive summation.

Calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values and using ordinary recursive summation.

Calculate the arithmetic mean of a single-precision floating-point strided array using pairwise summation.

Calculate the arithmetic mean of a single-precision floating-point strided array using extended accumulation.

Calculate the arithmetic mean of a double-precision floating-point strided array, ignoring NaN values and using a two-pass error correction algorithm.

Calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm.

Create an iterator which iteratively computes a cumulative arithmetic mean.

Calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values, using a two-pass error correction algorithm with extended accumulation, and returning an extended precision result.

Calculate the arithmetic mean of a single-precision floating-point strided array.

Calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation.

Calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation.

Calculate the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm.

Calculate the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring NaN values.

Calculate the arithmetic mean of a strided array, ignoring NaN values and using a two-pass error correction algorithm.

Calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values, using Welford's algorithm with extended accumulation, and returning an extended precision result.

Calculate the mean and variance of a double-precision floating-point strided array.

Calculate the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm.

Calculate the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm.

Compute the arithmetic mean of squared absolute values for all iterated values.

Create an iterator which iteratively computes a moving arithmetic mean of squared absolute values.

Now, you can calculate the sum, average, mode, median, range, variance, and standard deviation for the given array of numbers.

Transform stream factory to calculate arithmetic means for streamed data arrays (chunks).

Compute the arithmetic mean of absolute values for all iterated values.

Simple Array Math Library

Simple calculation of average values for an array of objects

Create an iterator which iteratively computes a moving arithmetic mean of absolute values.

mpony - find the min, max, avg or sum of numbers in an array

know the percentage of advance of an object

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Perform different actions with arrays.