# 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