partial derivative

The partial derivative of a multivariable function $f$ is simply its derivative with respect to only one variable, keeping all other variables constant (which are not functions of the variable in question). The formal definition is

D_{i}f(\mathbf{a})=\frac{\partial f}{\partial a_{i}}=\lim_{h\rightarrow 0}% \frac{1}{h}\left(f\left(\begin{array}[]{c}a_{1}\\ \vdots\\ a_{i}+h\\ \vdots\\ a_{n}\end{array}\right)-f\left(\mathbf{a}\right)\right)=\lim_{h\rightarrow 0}% \frac{f(\mathbf{a}+h\vec{e}_{i})-f(\mathbf{a})}{h}

where $\vec{e}_{i}$ is the standard basis vector of the $i$ th variable. Since this only affects the $i$ th variable, one can derive the function using common rules and tables, treating all other variables (which are not functions of $a_{i}$ ) as constants. For example, if $f(\mathbf{x})=x^{2}+2xy+y^{2}+y^{3}z$ , then

\begin{array}[]{lll}(1)&\frac{\partial f}{\partial x}=&2x+2y\\ &&\\ (2)&\frac{\partial f}{\partial y}=&2x+2y+3y^{2}z\\ &&\\ (3)&\frac{\partial f}{\partial z}=&y^{3}\end{array}

Note that in equation $(1)$ , we treated $y$ as a constant, since we were differentiating with respect to $x$ . $\left(\frac{d(c*x)}{dx}=c\right)$ The partial derivative of a vector-valued function $\vec{f}(\mathbf{x})$ with respect to variable $a_{i}$ is a vector $\overrightarrow{D_{i}\mathbf{f}}=\frac{\partial\vec{f}}{\partial a_{i}}$ .
Multiple Partials:
Multiple partial derivatives can be treated just like multiple derivatives. There is an additional degree of freedom though, as you can compound derivatives with respect to different variables. For example, using the above function,

\begin{array}[]{llll}(4)&\frac{\partial^{2}f}{\partial x^{2}}&=\frac{\partial}% {\partial x}(2x+2y)&=2\\ &&&\\ (5)&\frac{\partial^{2}f}{\partial z\partial y}&=\frac{\partial}{\partial z}(2x% +2y+3y^{2}z)&=3y^{2}\\ &&&\\ (6)&\frac{\partial^{2}f}{\partial y\partial z}&=\frac{\partial}{\partial y}(y^% {3})&=3y^{2}\end{array}

$D_{12}$ is another way of writing $\frac{\partial}{\partial x_{1}\partial x_{2}}$ . If $f(\mathbf{x})$ is continuous in the neighborhood of $\mathbf{x}$ , and $D_{ij}f$ and $D_{ji}f$ are continuous in an open set $V$ , it can be shown (see Clairaut’s theorem (http://planetmath.org/ClairautsTheorem)) that $D_{ij}f(\mathbf{x})=D_{ji}f(\mathbf{x})$ in $V$ , where $i, j$ are the ith and jth variables. In fact, as long as an equal number of partials are taken with respect to each variable, changing the order of differentiation will produce the same results in the above condition.
Another form of notation is $f^{(a,b,c,...)}(\mathbf{x})$ where $a$ is the partial derivative with respect to the first variable $a$ times, $b$ is the partial with respect to the second variable $b$ times, etc.

Title	partial derivative
Canonical name	PartialDerivative
Date of creation	2013-03-22 11:58:30
Last modified on	2013-03-22 11:58:30
Owner	Mathprof (13753)
Last modified by	Mathprof (13753)
Numerical id	26
Author	Mathprof (13753)
Entry type	Definition
Classification	msc 26B12
Related topic	Derivative2
Related topic	DerivativeNotation
Related topic	JacobianMatrix
Related topic	DirectionalDerivative
Related topic	Gradient
Related topic	HessianMatrix