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In calculus, integration by substitution, also known as u-substitution, reverse chain rule or change of variables,[1] is a method for evaluating integrals and antiderivatives. It is the counterpart to the chain rule for differentiation, and can loosely be thought of as using the chain rule "backwards."
Before stating the result rigorously, consider a simple case using indefinite integrals.
Compute
Set
where
This procedure is frequently used, but not all integrals are of a form that permits its use. In any event, the result should be verified by differentiating and comparing to the original integrand.
For definite integrals, the limits of integration must also be adjusted, but the procedure is mostly the same.
Let
In Leibniz notation, the substitution
The formula is used to transform one integral into another integral that is easier to compute. Thus, the formula can be read from left to right or from right to left in order to simplify a given integral. When used in the former manner, it is sometimes known as u-substitution or w-substitution in which a new variable is defined to be a function of the original variable found inside the composite function multiplied by the derivative of the inner function. The latter manner is commonly used in trigonometric substitution, replacing the original variable with a trigonometric function of a new variable and the original differential with the differential of the trigonometric function.
Integration by substitution can be derived from the fundamental theorem of calculus as follows. Let
and
in fact exist, and it remains to show that they are equal.
Since
Applying the fundamental theorem of calculus twice gives:
which is the substitution rule.
Consider the integral:
Make the substitution
Since the lower limit
Alternatively, one may fully evaluate the indefinite integral (see below) first then apply the boundary conditions. This becomes especially handy when multiple substitutions are used.
For the integral
The resulting integral can be computed using integration by parts or a double angle formula,
Substitution can be used to determine antiderivatives. One chooses a relation between
Similar to example 1 above, the following antiderivative can be obtained with this method:
where
There were no integral boundaries to transform, but in the last step reverting the original substitution
The tangent function can be integrated using substitution by expressing it in terms of the sine and cosine:
Using the substitution
The cotangent function can be integrated similarly by expressing it as
One may also use substitution when integrating functions of several variables.
Here, the substitution function (v1,...,vn) = φ(u1, ..., un) needs to be injective and continuously differentiable, and the differentials transform as:
where det(Dφ)(u1, ..., un) denotes the determinant of the Jacobian matrix of partial derivatives of φ at the point (u1, ..., un). This formula expresses the fact that the absolute value of the determinant of a matrix equals the volume of the parallelotope spanned by its columns or rows.
More precisely, the change of variables formula is stated in the next theorem:
Theorem. Let U be an open set in Rn and φ : U → Rn an injective differentiable function with continuous partial derivatives, the Jacobian of which is nonzero for every x in U. Then for any real-valued, compactly supported, continuous function f, with support contained in φ(U):
The conditions on the theorem can be weakened in various ways. First, the requirement that φ be continuously differentiable can be replaced by the weaker assumption that φ be merely differentiable and have a continuous inverse.[4] This is guaranteed to hold if φ is continuously differentiable by the inverse function theorem. Alternatively, the requirement that det(Dφ) ≠ 0 can be eliminated by applying Sard's theorem.[5]
For Lebesgue measurable functions, the theorem can be stated in the following form:[6]
Theorem. Let U be a measurable subset of Rn and φ : U → Rn an injective function, and suppose for every x in U there exists φ′(x) in Rn,n such that φ(y) = φ(x) + φ′(x)(y − x) + o(||y − x||) as y → x (here o is little-o notation). Then φ(U) is measurable, and for any real-valued function f defined on φ(U):
Another very general version in measure theory is the following:[7]
Theorem. Let X be a locally compact Hausdorff space equipped with a finite Radon measure μ, and let Y be a σ-compact Hausdorff space with a σ-finite Radon measure ρ. Let φ : X → Y be an absolutely continuous function (where the latter means that ρ(φ(E)) = 0 whenever μ(E) = 0). Then there exists a real-valued Borel measurable function w on X such that for every Lebesgue integrable function f : Y → R, the function (f ∘ φ) ⋅ w is Lebesgue integrable on X, and
In geometric measure theory, integration by substitution is used with Lipschitz functions. A bi-Lipschitz function is a Lipschitz function φ : U → Rn which is injective and whose inverse function φ−1 : φ(U) → U is also Lipschitz. By Rademacher's theorem, a bi-Lipschitz mapping is differentiable almost everywhere. In particular, the Jacobian determinant of a bi-Lipschitz mapping det Dφ is well-defined almost everywhere. The following result then holds:
Theorem. Let U be an open subset of Rn and φ : U → Rn be a bi-Lipschitz mapping. Let f : φ(U) → R be measurable. Then
The above theorem was first proposed by Euler when he developed the notion of double integrals in 1769. Although generalized to triple integrals by Lagrange in 1773, and used by Legendre, Laplace, and Gauss, and first generalized to n variables by Mikhail Ostrogradsky in 1836, it resisted a fully rigorous formal proof for a surprisingly long time, and was first satisfactorily resolved 125 years later, by Élie Cartan in a series of papers beginning in the mid-1890s.[8][9]
Substitution can be used to answer the following important question in probability: given a random variable X with probability density pX and another random variable Y such that Y= ϕ(X) for injective (one-to-one) ϕ, what is the probability density for Y?
It is easiest to answer this question by first answering a slightly different question: what is the probability that Y takes a value in some particular subset S? Denote this probability P(Y ∈ S). Of course, if Y has probability density pY, then the answer is:
but this is not really useful because we do not know pY; it is what we are trying to find. We can make progress by considering the problem in the variable X. Y takes a value in S whenever X takes a value in
Changing from variable x to y gives:
Combining this with our first equation gives:
so:
In the case where X and Y depend on several uncorrelated variables (i.e.,
es:Métodos de integración#Método de integración por sustitución
![]() | Original source: https://en.wikipedia.org/wiki/Integration by substitution.
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