Inverse of Vandermonde Matrix/Corollary
Jump to navigation
Jump to search
![]() | This page has been identified as a candidate for refactoring of medium complexity. Until this has been finished, please leave {{Refactor}} in the code.
New contributors: Refactoring is a task which is expected to be undertaken by experienced editors only. Because of the underlying complexity of the work needed, it is recommended that you do not embark on a refactoring task until you have become familiar with the structural nature of pages of $\mathsf{Pr} \infty \mathsf{fWiki}$.To discuss this page in more detail, feel free to use the talk page. When this work has been completed, you may remove this instance of {{Refactor}} from the code. |
Corollary to Inverse of Vandermonde Matrix
Define for variables $\set {y_1,\ldots, y_k}$ elementary symmetric functions:
\(\ds \map {e_m} {\set {y_1, \ldots, y_k} }\) | \(=\) | \(\ds \sum_{1 \mathop \le j_1 \mathop < j_2 \mathop < \mathop \cdots \mathop < j_m \mathop \le k } y_{j_1} y_{j_2} \cdots y_{j_m}\) | for $m = 0, 1, \ldots, k$ |
Let $\set {x_1, \ldots, x_n}$ be a set of distinct values.
Let $W_n$ and $V_n$ be Vandermonde matrices of order $n$:
- $W_n = \begin{bmatrix} 1 & x_1 & \cdots & x_1^{n-1} \\ 1 & x_2 & \cdots & x_2^{n-1} \\ \vdots & \vdots & \ddots & \vdots \\ 1 & x_1^{n-1} & \cdots & x_n^{n-1} \\ \end{bmatrix}, \quad V_n = \begin{bmatrix} x_1 & x_2 & \cdots & x_n \\ x_1^2 & x_2^2 & \cdots & x_n^2 \\ \vdots & \vdots & \ddots & \vdots \\ x_1^n & x_2^n & \cdots & x_n^n \\ \end{bmatrix}$
Let their matrix inverses be written as $W_n^{-1} = \begin{bmatrix} b_{ij} \end{bmatrix}$ $V_n^{-1} = \begin{bmatrix} c_{ij} \end{bmatrix}$.
Then:
\(\ds b_{ij}\) | \(=\) | \(\ds \dfrac {\paren {-1}^{n - i} \map {e_{n - i} } {\set {x_1, \ldots, x_n} \setminus \set {x_j} } } {\prod_{m \mathop = 1, m \mathop \ne j }^n \paren {x_j - x_m} }\) | for $i, j = 1, \ldots, n$ | |||||||||||
\(\ds c_{ij}\) | \(=\) | \(\ds \dfrac 1 {x_i} \, b_{j i}\) | for $i, j = 1, \ldots, n$ |
Proof
The details appear in Inverse of Vandermonde Matrix/Proof 1, same notation. $\blacksquare$