X Vector in 2nd Order Taylor Series Formula w/ Hessian Matrix

In summary, the formula for a Taylor Series approximation of the second order at point (a,b) includes the function value at (a,b), the gradient of the function at (a,b) multiplied by the x-vector, and the Hessian matrix of the function at (a,b) multiplied by the quadratic term (x-a, y-b). The Hessian matrix contains the second partial derivatives of the function and the x-vector is represented by <x-a, y-b>.
  • #1
jaguar7
42
0
The formula given by my instructor for a Taylor Series approximation of the second order at point (a,b) is f(a,b) + grad(f(a,b))x + 1/2 H(f(a,b)) x

If you recognize this formula, do you know what the x vector is?

Note: x is the x-vector, and H represents the Hessian Matrix. Thanks!

The Hessian Matrix is the matrix with values [fxx, fxy, fyx, and fyy], where fxx represents the second partial derivative. Not sure the proper terminology for it... df^2 / (dx)^2 (where d is a delta (not d) to represent partial dif.)
 
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  • #2


x is the vector <x- a, y- b>. And you need a quadratic in the second term- it should be
[tex]f(a, b)+ \begin{bmatrix}\frac{\partial f}{\partial x}(a, b) & \frac{\partial f}{\partial y}(a, b)\end{bmatrix}\begin{bmatrix}x- a \\ y- b\end{bmatrix}+ \frac{1}{2}\begin{bmatrix}x- a & y- b\end{bmatrix}\begin{bmatrix}\frac{\partial^2 f}{\partial x^2}(a,b) & \frac{\partial^2 f}{\partial x\partial y}(a,b) \\ \frac{\partial^2 f}{\partial x\partial y}(a,b) & \frac{\partial^2 f}{\partial y^2}(a,b)\end{bmatrix}\begin{bmatrix} x- a \\ y- b\end{bmatrix}[/tex]
 

FAQ: X Vector in 2nd Order Taylor Series Formula w/ Hessian Matrix

What is X Vector in 2nd Order Taylor Series Formula?

The X Vector in 2nd Order Taylor Series Formula refers to the input variables or parameters used in the second-order Taylor series approximation of a multivariable function. It is a vector that contains the values of each variable at a specific point in the function.

How is the X Vector used in the 2nd Order Taylor Series Formula?

The X Vector is used to calculate the second-order Taylor series approximation of a multivariable function at a specific point. It is plugged into the formula along with the function's partial derivatives and the Hessian matrix to approximate the function's value at that point.

What is the Hessian Matrix in the 2nd Order Taylor Series Formula?

The Hessian Matrix is a matrix of second-order partial derivatives of a multivariable function. It represents the curvature of the function at a specific point and is used in the 2nd Order Taylor Series Formula to improve the accuracy of the approximation.

How is the Hessian Matrix related to the X Vector in the 2nd Order Taylor Series Formula?

The Hessian Matrix and the X Vector are both used in the 2nd Order Taylor Series Formula to approximate the value of a multivariable function at a specific point. The X Vector provides the input values, while the Hessian Matrix represents the curvature of the function at that point.

Why is the 2nd Order Taylor Series Formula important in scientific research?

The 2nd Order Taylor Series Formula is important in scientific research because it allows for the approximation of complex multivariable functions using only their partial derivatives. This can be useful in various fields such as physics, engineering, and economics, where it is often necessary to approximate functions to make predictions and solve problems.

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