Function

Static Public Summary
public	choose(n: number, k: number): number Choose k elements from a set of n elements.
public	error(x: number): number A useful function.
public	factorial(n: number): number n! is the product of all positive integers less than or equal to n.
public	gamma(n: number): number The gamma function is a useful general function.
public	gammainc_lower(s: number, z: number): number The regularized lower incomplete gamma function See
public	lngamma(z: number): number The log-gamma function is a useful general function.
public	mean(x: Array<number>): number Averages a list of elements.
public	median(x: Array<number>): number Finds the central most value for a list of numbers.
public	mode(x: Array<number>): number Finds the most frequent values of a list of numbers.
public	percentile(x: Array<number>, p: number): number Finds the element of a list of numbers at a certain percentile ordered smallest to largest.
public	quantile(x: Array<number>, quantiles: Array<number>): number Finds the nth largest element of a list of numbers.
public	range(x: Array<number>): number Finds the difference between the largest and smallest values.
public	select(x: Array<number>, k: number, begin: number, end: number): number Efficiently finds the kth largest element in a array.
public	std(x: Array<number>): number A measure that is used to quantify the amount of variation of a set of data values.
public	stirling(n: number): number Efficiently appoximates ln(n!).
public	sum(x: Array<number>): number Adds a list of elements together.
public	sumNthPowerDev(x: Array<number>, n: number, absolute: boolean): number A really useful function.
public	ttest(sample: Sample, other: Sample, x: number): number Computes Student's T-Test for the provided samples. If only one sample is provided, a one-sample t-test is computed on the sample mean vs x. If two samples are provided, a two-sample t-test is computed on the difference between the sample means and x. See: Student's T-Test
public	variance(x: Array<number>): number A measure that is used to quantify the amount of variation of a set of data values from their mean value.
public	zscore(x: number, mu: number, std: number): number The signed number of deviations an observed value is above the mean.

Static Public

public choose(n: number, k: number): number source

import choose from 'sampson/lib/utils/choose.js'

Choose k elements from a set of n elements. See: Binomial Coefficient

Params:

Name	Type	Attribute	Description
n	number		The number of elements to choose from.
k	number		The number of elements to choose.

Return:

number

A binomial coefficient or NaN if n < k.

public error(x: number): number source

import error from 'sampson/lib/utils/error.js'

A useful function. Gets used in the Normal distribution cdf. It's the probability of a random variable with normal distribution of mean 0 and variance 1/2 falling in the range [-x, x]. See: Error

Params:

Name	Type	Attribute	Description
x	number		The numbers to average.

Return:

number

The error value.

public factorial(n: number): number source

import factorial from 'sampson/lib/utils/factorial.js'

n! is the product of all positive integers less than or equal to n. See

Params:

Name	Type	Attribute	Description
n	number		The number.

Return:

number

n!, or 1 if n == 0, or Inifinity if n > ~170, or NaN if n < 0.

public gamma(n: number): number source

import gamma from 'sampson/lib/utils/gamma.js'

The gamma function is a useful general function. It's (n - 1)!. See

Params:

Name	Type	Attribute	Description
n	number		The number.

Return:

number

An approximation of (n-1)! or Infinity if n is a negative integer.

public gammainc_lower(s: number, z: number): number source

import gammainc_lower from 'sampson/lib/utils/gammainc.js'

The regularized lower incomplete gamma function See

Params:

Name	Type	Attribute	Description
s	number		The first number.
z	number		The second number.

Return:

number

The value from the lower incomplete gamma function.

public lngamma(z: number): number source

import lngamma from 'sampson/lib/utils/lngamma.js'

The log-gamma function is a useful general function. It can handle much larger numbers because it grows much slower compared to the gamma function. It's (n - 1)! and is used by the gamma function for n > 100. See

Params:

Name	Type	Attribute	Description
z	number		The number.

Return:

number

An approximation of ln(n-1)! or NaN if n < 0.

public mean(x: Array<number>): number source

import mean from 'sampson/lib/utils/mean.js'

Averages a list of elements. Uses our internal sum function. See: Mean

Params:

Name	Type	Attribute	Description
x	Array<number>		The numbers to average.

Return:

number

The mean or NaN if x is the empty set.

public median(x: Array<number>): number source

import median from 'sampson/lib/utils/median.js'

Finds the central most value for a list of numbers. If the list is even, and has no single center, the two inner-most values are averaged. Uses our internal selection function. See: Median

Params:

Name	Type	Attribute	Description
x	Array<number>		The numbers.

Return:

number

The median or NaN if x is the empty set.

public mode(x: Array<number>): number source

import mode from 'sampson/lib/utils/mode.js'

Finds the most frequent values of a list of numbers. It always returns an array. The result may contain one or more values. See: Mode

Params:

Name	Type	Attribute	Description
x	Array<number>		The numbers.

Return:

number

The mode or NaN if x is the empty set.

public percentile(x: Array<number>, p: number): number source

import percentile from 'sampson/lib/utils/percentile.js'

Finds the element of a list of numbers at a certain percentile ordered smallest to largest. Uses the internal select function. See: List Ranking

Params:

Name	Type	Attribute	Description
x	Array<number>		The numbers.
p	number		The percentile.

Return:

number

The element at the pth percentile of x or NaN if x is the empty set.

public quantile(x: Array<number>, quantiles: Array<number>): number source

import quantile from 'sampson/lib/utils/quantile.js'

Finds the nth largest element of a list of numbers. Accepts both a single quantile and an array of quantiles. See: List Ranking

Params:

Name	Type	Attribute	Description
x	Array<number>		The numbers.
quantiles	Array<number>		A list of quantiles to compute.

Return:

number

The computed quantiles respective to quantiles provided or NaN if x is the empty set.

public range(x: Array<number>): number source

import range from 'sampson/lib/utils/range.js'

Finds the difference between the largest and smallest values. See: Range)

Params:

Name	Type	Attribute	Description
x	Array<number>		The numbers.

Return:

number

The range or NaN if x is the empty set.

public select(x: Array<number>, k: number, begin: number, end: number): number source

import select from 'sampson/lib/utils/select.js'

Efficiently finds the kth largest element in a array. See: Selection

Params:

Name	Type	Attribute	Description
x	Array<number>		The numbers.
k	number		The element to select.
begin	number	optional	The starting index.
end	number	optional	The ending index.

Return:

number

The kth largest element or NaN if x is the empty set.

public std(x: Array<number>): number source

import std from 'sampson/lib/utils/std.js'

A measure that is used to quantify the amount of variation of a set of data values. See: Standard Deviation

Params:

Name	Type	Attribute	Description
x	Array<number>		The numbers.

Return:

number

The standard deviation or 0 if x is the empty set.

public stirling(n: number): number source

import stirling from 'sampson/lib/utils/stirling.js'

Efficiently appoximates ln(n!). Similar to the gamma function, but can be faster and more accurate. See: Stirling's Approximation

Params:

Name	Type	Attribute	Description
n	number		The number.

Return:

number

An approximation on ln(n!).

public sum(x: Array<number>): number source

import sum from 'sampson/lib/utils/sum.js'

Adds a list of elements together. Uses the Kahan summation algorithm to compensate for floating-point error. See: Summation

Params:

Name	Type	Attribute	Description
x	Array<number>		The numbers.

Return:

number

The sum or 0 if x is the empty set.

public sumNthPowerDev(x: Array<number>, n: number, absolute: boolean): number source

import sumNthPowerDev from 'sampson/lib/utils/sumnthpowerdev.js'

A really useful function. Takes a set of observations and returns the sum of the difference of each observation and the mean of the set raised to the nth power. Can be used to find the absolute value of the difference for functions like MeanDeviation, or by default, the signed values for functions like Variance and SquaredMeanDeviation.

Params:

Name	Type	Attribute	Description
x	Array<number>		The numbers.
n	number		The number to raise to.
absolute	boolean	optional default: false	Use absolute value of difference.

Return:

number

The sum of (x-mu)^n or NaN if x is the empty set.

public ttest(sample: Sample, other: Sample, x: number): number source

import ttest from 'sampson/lib/statistics/ttest.js'

Computes Student's T-Test for the provided samples. If only one sample is provided, a one-sample t-test is computed on the sample mean vs x. If two samples are provided, a two-sample t-test is computed on the difference between the sample means and x. See: Student's T-Test

Params:

Name	Type	Attribute	Description
sample	Sample		The sample to test
other	Sample	optional	An optional sample to compare with a two sample test.
x	number	optional default: 0	The mean or difference to test.

Return:

number

The t-statistic or NaN if the sample is the empty set.

public variance(x: Array<number>): number source

import variance from 'sampson/lib/utils/variance.js'

A measure that is used to quantify the amount of variation of a set of data values from their mean value. See: Variance

Params:

Name	Type	Attribute	Description
x	Array<number>		The numbers.

Return:

number

The variance or NaN if x is the empty set.

public zscore(x: number, mu: number, std: number): number source

import zscore from 'sampson/lib/utils/zscore.js'

The signed number of deviations an observed value is above the mean. See: Standard Score

Params:

Name	Type	Attribute	Description
x	number		The number.
mu	number		The mean.
std	number		The standard deviation.

Return:

number

The zscore.