Compute Matrix Inverse

curl --request POST \
  --url https://finceptbackend.share.zrok.io/quantlib/numerical/linalg/inverse \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: <api-key>' \
  --data '
{
  "A": [
    [
      4,
      7
    ],
    [
      2,
      6
    ]
  ]
}
'

{
  "success": true,
  "data": {
    "inverse": [
      [
        0.6,
        -0.7
      ],
      [
        -0.2,
        0.4
      ]
    ]
  }
}

quantlib-numerical

Compute Matrix Inverse

Compute the inverse of a square non-singular matrix A such that A × A⁻¹ = I (identity matrix). Matrix must be square and non-singular (determinant ≠ 0). Uses LU decomposition for numerical stability. Used in portfolio optimization, covariance matrix inversion, solving multiple systems with the same coefficient matrix, and coordinate transformations. Note: For solving Ax=b, direct solving is more efficient than computing A⁻¹ and multiplying.

POST

quantlib

numerical

linalg

inverse

Compute Matrix Inverse

curl --request POST \
  --url https://finceptbackend.share.zrok.io/quantlib/numerical/linalg/inverse \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: <api-key>' \
  --data '
{
  "A": [
    [
      4,
      7
    ],
    [
      2,
      6
    ]
  ]
}
'

{
  "success": true,
  "data": {
    "inverse": [
      [
        0.6,
        -0.7
      ],
      [
        -0.2,
        0.4
      ]
    ]
  }
}

Authorizations

X-API-Key

string

header

required

API key for authentication. Get your key at https://finceptbackend.share.zrok.io/auth/register

Body

application/json

number[][]

required

Square non-singular matrix (n × n)

Example:

[[4, 7], [2, 6]]

Response

Successful Response

success

boolean

Example:

true

data

object

Show child attributes

Solve Least Squares Problem

Solve Ordinary Differential Equation (ODE)

⌘I

Free Tier

Basic Tier

Standard Tier

Pro Tier

Compute Matrix Inverse

Authorizations

Body

Response