Implicit Differentiation

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## Examples

### Inverse functions

### Algebraic functions

## Caveats

## Implicit differentiation

### Examples

### General formula for derivative of implicit function

## Implicit function theorem

## In algebraic geometry

## In differential equations

## Applications in economics

### Marginal rate of substitution

### Marginal rate of technical substitution

### Optimization

## See also

## References

## Further reading

## External links

This article uses material from the Wikipedia page available here. It is released under the Creative Commons Attribution-Share-Alike License 3.0.

Implicit Differentiation

In mathematics, an **implicit equation** is a relation of the form *R*(*x*_{1},..., *x _{n}*) = 0, where R is a function of several variables (often a polynomial). For example, the implicit equation of the unit circle is

An **implicit function** is a function that is defined implicitly by an implicit equation, by associating one of the variables (the value) with the others (the arguments).^{[1]}^{:204-206} Thus, an implicit function for y in the context of the unit circle is defined implicitly by *x*^{2} + *f*(*x*)^{2} - 1 = 0. This implicit equation defines f as a function of x only if -1 x and one considers only non-negative (or non-positive) values for the values of the function.

The implicit function theorem provides conditions under which some kinds of relations define an implicit function, namely relations defined as the indicator function of the zero set of some continuously differentiable multivariate function.

A common type of implicit function is an inverse function. Not all functions have a unique inverse function. If g is a function of x that has a unique inverse, then the inverse function of g, called *g*^{-1}, is the unique function giving a solution of the equation

for x in terms of y. This solution can then be written as

Defining *g*^{-1} as the inverse of g is an implicit definition. For some functions g, *g*^{-1}(*y*) can be written out explicitly as a closed-form expression -- for instance, if *g*(*x*) = 2*x* - 1, then *g*^{-1}(*y*) = (*y* + 1). However, this is often not possible, or only by introducing a new notation (as in the product log example below).

Intuitively, an inverse function is obtained from g by interchanging the roles of the dependent and independent variables.

**Example.**The product log is an implicit function giving the solution for x of the equation*y*-*xe*^{x}= 0.

An **algebraic function** is a function that satisfies a polynomial equation whose coefficients are themselves polynomials. For example, an algebraic function in one variable x gives a solution for y of an equation

where the coefficients *a _{i}*(

Algebraic functions play an important role in mathematical analysis and algebraic geometry. A simple example of an algebraic function is given by the left side of the unit circle equation:

Solving for y gives an explicit solution:

But even without specifying this explicit solution, it is possible to refer to the implicit solution of the unit circle equation as *y* = *f*(*x*), where f is the multi-valued implicit function.

While explicit solutions can be found for equations that are quadratic, cubic, and quartic in y, the same is not in general true for quintic and higher degree equations, such as

Nevertheless, one can still refer to the implicit solution *y* = *f*(*x*) involving the multi-valued implicit function f.

Not every equation *R*(*x*, *y*) = 0 implies a graph of a single-valued function, the circle equation being one prominent example. Another example is an implicit function given by *x* - *C*(*y*) = 0 where C is a cubic polynomial having a "hump" in its graph. Thus, for an implicit function to be a *true* (single-valued) function it might be necessary to use just part of the graph. An implicit function can sometimes be successfully defined as a true function only after "zooming in" on some part of the x-axis and "cutting away" some unwanted function branches. Then an equation expressing y as an implicit function of the other variables can be written.

The defining equation *R*(*x*, *y*) = 0 can also have other pathologies. For example, the equation *x* = 0 does not imply a function *f*(*x*) giving solutions for y at all; it is a vertical line. In order to avoid a problem like this, various constraints are frequently imposed on the allowable sorts of equations or on the domain. The implicit function theorem provides a uniform way of handling these sorts of pathologies.

In calculus, a method called **implicit differentiation** makes use of the chain rule to differentiate implicitly defined functions.

To differentiate an implicit function *y*(*x*), defined by an equation *R*(*x*, *y*) = 0, it is not generally possible to solve it explicitly for y and then differentiate. Instead, one can totally differentiate *R*(*x*, *y*) = 0 with respect to x and y and then solve the resulting linear equation for to explicitly get the derivative in terms of x and y. Even when it is possible to explicitly solve the original equation, the formula resulting from total differentiation is, in general, much simpler and easier to use.

**Example 1.** Consider

This equation is easy to solve for y, giving

where the right side is the explicit form of the function *y*(*x*). Differentiation then gives = -1.

Alternatively, one can totally differentiate the original equation:

Solving for gives

the same answer as obtained previously.

**Example 2.** An example of an implicit function for which implicit differentiation is easier than using explicit differentiation is the function *y*(*x*) defined by the equation

To differentiate this explicitly with respect to x, one has first to get

and then differentiate this function. This creates two derivatives: one for *y* >= 0 and another for *y* < 0.

It is substantially easier to implicitly differentiate the original equation:

giving

**Example 3.** Often, it is difficult or impossible to solve explicitly for y, and implicit differentiation is the only feasible method of differentiation. An example is the equation

It is impossible to algebraically express y explicitly as a function of x, and therefore one cannot find by explicit differentiation. Using the implicit method, can be obtained by differentiating the equation to obtain

where = 1. Factoring out shows that

which yields the result

which is defined for

If *R*(*x*, *y*) = 0, the derivative of the implicit function *y*(*x*) is given by^{[2]}^{:§11.5}

where *R _{x}* and

The above formula comes from using the generalized chain rule to obtain the total derivative -- with respect to x -- of both sides of *R*(*x*, *y*) = 0:

hence

which, when solved for , gives the expression above.

Let *R*(*x*, *y*) be a differentiable function of two variables, and (*a*, *b*) be a pair of real numbers such that *R*(*a*, *b*) = 0. If ? 0, then *R*(*x*, *y*) = 0 defines an implicit function that is differentiable in some small enough neighbourhood of (*a*, *b*); in other words, there is a differentiable function f that is defined and differentiable in some neighbourhood of a, such that *R*(*x*, *f*(*x*)) = 0 for x in this neighbourhood.

The condition ? 0 means that (*a*, *b*) is a regular point of the implicit curve of implicit equation *R*(*x*, *y*) = 0 where the tangent is not vertical.

In a less technical language, implicit functions exist and can be differentiated, if the curve has a non-vertical tangent.^{[2]}^{:§11.5}

Consider a relation of the form *R*(*x*_{1},..., *x*_{n}) = 0, where R is a multivariable polynomial. The set of the values of the variables that satisfy this relation is called an implicit curve if *n* = 2 and an **implicit surface** if *n* = 3. The implicit equations are the basis of algebraic geometry, whose basic subjects of study are the simultaneous solutions of several implicit equations whose left-hand sides are polynomials. These sets of simultaneous solutions are called affine algebraic sets.

The solutions of differential equations generally appear expressed by an implicit function.^{[3]}

In economics, when the level set *R*(*x*, *y*) = 0 is an indifference curve for the quantities x and y consumed of two goods, the absolute value of the implicit derivative is interpreted as the marginal rate of substitution of the two goods: how much more of y one must receive in order to be indifferent to a loss of one unit of x.

Similarly, sometimes the level set *R*(*L*, *K*) is an isoquant showing various combinations of utilized quantities L of labor and K of physical capital each of which would result in the production of the same given quantity of output of some good. In this case the absolute value of the implicit derivative is interpreted as the marginal rate of technical substitution between the two factors of production: how much more capital the firm must use to produce the same amount of output with one less unit of labor.

Often in economic theory, some function such as a utility function or a profit function is to be maximized with respect to a choice vector x even though the objective function has not been restricted to any specific functional form. The implicit function theorem guarantees that the first-order conditions of the optimization define an implicit function for each element of the optimal vector *x** of the choice vector x. When profit is being maximized, typically the resulting implicit functions are the labor demand function and the supply functions of various goods. When utility is being maximized, typically the resulting implicit functions are the labor supply function and the demand functions for various goods.

Moreover, the influence of the problem's parameters on *x** -- the partial derivatives of the implicit function -- can be expressed as total derivatives of the system of first-order conditions found using total differentiation.

**^**Chiang, Alpha C. (1984).*Fundamental Methods of Mathematical Economics*(Third ed.). New York: McGraw-Hill. ISBN 0-07-010813-7.- ^
^{a}^{b}Stewart, James (1998).*Calculus Concepts And Contexts*. Brooks/Cole Publishing Company. ISBN 0-534-34330-9. **^**Kaplan, Wilfred (2003).*Advanced Calculus*. Boston: Addison-Wesley. ISBN 0-201-79937-5.

- Binmore, K. G. (1983). "Implicit Functions".
*Calculus*. New York: Cambridge University Press. pp. 198-211. ISBN 0-521-28952-1. - Rudin, Walter (1976).
*Principles of Mathematical Analysis*. Boston: McGraw-Hill. pp. 223-228. ISBN 0-07-054235-X. - Simon, Carl P.; Blume, Lawrence (1994). "Implicit Functions and Their Derivatives".
*Mathematics for Economists*. New York: W. W. Norton. pp. 334-371. ISBN 0-393-95733-0.

- "Implicit Differentiation, What's Going on Here?".
*3Blue1Brown*. Essence of Calculus. May 3, 2017 – via YouTube.

This article uses material from the Wikipedia page available here. It is released under the Creative Commons Attribution-Share-Alike License 3.0.

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