function varc
varc(
x: array,
flag?: 0 | 1,
dim?: 0 | 1,
): number

Computes the variance.

Computes the variance (average squared deviation from mean) for arrays or matrices. Supports both population (N) and sample (N-1) normalizations.

Examples

Sample variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3]), 1);

Population variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3], 0), 0.6666666666666666);

Matrix variance along rows (default dim=0, flag=1)

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([[1, 2], [3, 4]]), [[0.5, 0.5]]);

Parameters

x: array

Input array or matrix

optional
flag: 0 | 1

Normalization type (0: population, 1: sample). Default is 1

optional
dim: 0 | 1

Dimension to operate on (0: rows, 1: columns). Default is 0

Return Type

number

Computed variance values

Throws

When input is invalid

varc(
x: matrix,
flag?: 0 | 1,
dim?: 0 | 1,
): matrix

Computes the variance.

Computes the variance (average squared deviation from mean) for arrays or matrices. Supports both population (N) and sample (N-1) normalizations.

Examples

Sample variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3]), 1);

Population variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3], 0), 0.6666666666666666);

Matrix variance along rows (default dim=0, flag=1)

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([[1, 2], [3, 4]]), [[0.5, 0.5]]);

Parameters

Input array or matrix

optional
flag: 0 | 1

Normalization type (0: population, 1: sample). Default is 1

optional
dim: 0 | 1

Dimension to operate on (0: rows, 1: columns). Default is 0

Return Type

Computed variance values

Throws

When input is invalid

varc(
x: array,
flag: 0 | 1,
dim?: 0 | 1,
): number

Computes the variance.

Computes the variance (average squared deviation from mean) for arrays or matrices. Supports both population (N) and sample (N-1) normalizations.

Examples

Sample variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3]), 1);

Population variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3], 0), 0.6666666666666666);

Matrix variance along rows (default dim=0, flag=1)

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([[1, 2], [3, 4]]), [[0.5, 0.5]]);

Parameters

x: array

Input array or matrix

flag: 0 | 1

Normalization type (0: population, 1: sample). Default is 1

optional
dim: 0 | 1

Dimension to operate on (0: rows, 1: columns). Default is 0

Return Type

number

Computed variance values

Throws

When input is invalid

varc(
x: matrix,
flag: 0 | 1,
dim?: 0 | 1,
): matrix

Computes the variance.

Computes the variance (average squared deviation from mean) for arrays or matrices. Supports both population (N) and sample (N-1) normalizations.

Examples

Sample variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3]), 1);

Population variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3], 0), 0.6666666666666666);

Matrix variance along rows (default dim=0, flag=1)

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([[1, 2], [3, 4]]), [[0.5, 0.5]]);

Parameters

Input array or matrix

flag: 0 | 1

Normalization type (0: population, 1: sample). Default is 1

optional
dim: 0 | 1

Dimension to operate on (0: rows, 1: columns). Default is 0

Return Type

Computed variance values

Throws

When input is invalid

varc(
x: array,
flag: 0 | 1,
dim: 0 | 1,
): number

Computes the variance.

Computes the variance (average squared deviation from mean) for arrays or matrices. Supports both population (N) and sample (N-1) normalizations.

Examples

Sample variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3]), 1);

Population variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3], 0), 0.6666666666666666);

Matrix variance along rows (default dim=0, flag=1)

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([[1, 2], [3, 4]]), [[0.5, 0.5]]);

Parameters

x: array

Input array or matrix

flag: 0 | 1

Normalization type (0: population, 1: sample). Default is 1

dim: 0 | 1

Dimension to operate on (0: rows, 1: columns). Default is 0

Return Type

number

Computed variance values

Throws

When input is invalid

varc(
x: matrix,
flag: 0 | 1,
dim: 0 | 1,
): matrix

Computes the variance.

Computes the variance (average squared deviation from mean) for arrays or matrices. Supports both population (N) and sample (N-1) normalizations.

Examples

Sample variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3]), 1);

Population variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3], 0), 0.6666666666666666);

Matrix variance along rows (default dim=0, flag=1)

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([[1, 2], [3, 4]]), [[0.5, 0.5]]);

Parameters

Input array or matrix

flag: 0 | 1

Normalization type (0: population, 1: sample). Default is 1

dim: 0 | 1

Dimension to operate on (0: rows, 1: columns). Default is 0

Return Type

Computed variance values

Throws

When input is invalid

varc(
flag?: 0 | 1,
dim?: 0 | 1,
): number | matrix

Computes the variance.

Computes the variance (average squared deviation from mean) for arrays or matrices. Supports both population (N) and sample (N-1) normalizations.

Examples

Sample variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3]), 1);

Population variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3], 0), 0.6666666666666666);

Matrix variance along rows (default dim=0, flag=1)

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([[1, 2], [3, 4]]), [[0.5, 0.5]]);

Parameters

Input array or matrix

optional
flag: 0 | 1

Normalization type (0: population, 1: sample). Default is 1

optional
dim: 0 | 1

Dimension to operate on (0: rows, 1: columns). Default is 0

Return Type

number | matrix

Computed variance values

Throws

When input is invalid

varc(
flag: 0 | 1,
dim?: 0 | 1,
): number | matrix

Computes the variance.

Computes the variance (average squared deviation from mean) for arrays or matrices. Supports both population (N) and sample (N-1) normalizations.

Examples

Sample variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3]), 1);

Population variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3], 0), 0.6666666666666666);

Matrix variance along rows (default dim=0, flag=1)

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([[1, 2], [3, 4]]), [[0.5, 0.5]]);

Parameters

Input array or matrix

flag: 0 | 1

Normalization type (0: population, 1: sample). Default is 1

optional
dim: 0 | 1

Dimension to operate on (0: rows, 1: columns). Default is 0

Return Type

number | matrix

Computed variance values

Throws

When input is invalid

varc(
flag: 0 | 1,
dim: 0 | 1,
): number | matrix

Computes the variance.

Computes the variance (average squared deviation from mean) for arrays or matrices. Supports both population (N) and sample (N-1) normalizations.

Examples

Sample variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3]), 1);

Population variance

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([1, 2, 3], 0), 0.6666666666666666);

Matrix variance along rows (default dim=0, flag=1)

import { assertEquals } from "jsr:@std/assert";

assertEquals(varc([[1, 2], [3, 4]]), [[0.5, 0.5]]);

Parameters

Input array or matrix

flag: 0 | 1

Normalization type (0: population, 1: sample). Default is 1

dim: 0 | 1

Dimension to operate on (0: rows, 1: columns). Default is 0

Return Type

number | matrix

Computed variance values

Throws

When input is invalid

Usage

import varc from "stats/varc.ts";