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  2. Multivariable calculus - Wikipedia

    en.wikipedia.org/wiki/Multivariable_calculus

    The partial derivative generalizes the notion of the derivative to higher dimensions. A partial derivative of a multivariable function is a derivative with respect to one variable with all other variables held constant. [1]: 26ff A partial derivative may be thought of as the directional derivative of the function along a coordinate axis.

  3. Chain rule - Wikipedia

    en.wikipedia.org/wiki/Chain_rule

    t. e. In calculus, the chain rule is a formula that expresses the derivative of the composition of two differentiable functions f and g in terms of the derivatives of f and g. More precisely, if is the function such that for every x, then the chain rule is, in Lagrange's notation, or, equivalently, The chain rule may also be expressed in ...

  4. Partial derivative - Wikipedia

    en.wikipedia.org/wiki/Partial_derivative

    e. In mathematics, a partial derivative of a function of several variables is its derivative with respect to one of those variables, with the others held constant (as opposed to the total derivative, in which all variables are allowed to vary). Partial derivatives are used in vector calculus and differential geometry.

  5. Matrix calculus - Wikipedia

    en.wikipedia.org/wiki/Matrix_calculus

    Miscellanea. v. t. e. In mathematics, matrix calculus is a specialized notation for doing multivariable calculus, especially over spaces of matrices. It collects the various partial derivatives of a single function with respect to many variables, and/or of a multivariate function with respect to a single variable, into vectors and matrices that ...

  6. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    Numerical differentiation. Use of numerical analysis to estimate derivatives of functions. Finite difference estimation of derivative. In numerical analysis, numerical differentiation algorithms estimate the derivative of a mathematical function or function subroutine using values of the function and perhaps other knowledge about the function.

  7. Second partial derivative test - Wikipedia

    en.wikipedia.org/wiki/Second_partial_derivative_test

    Second partial derivative test. The Hessian approximates the function at a critical point with a second-degree polynomial. In mathematics, the second partial derivative test is a method in multivariable calculus used to determine if a critical point of a function is a local minimum, maximum or saddle point.

  8. Product rule - Wikipedia

    en.wikipedia.org/wiki/Product_rule

    Calculus. In calculus, the product rule (or Leibniz rule[1] or Leibniz product rule) is a formula used to find the derivatives of products of two or more functions. For two functions, it may be stated in Lagrange's notation as or in Leibniz's notation as.

  9. Differentiation rules - Wikipedia

    en.wikipedia.org/wiki/Differentiation_rules

    The derivatives in the table above are for when the range of the inverse secant is [,] and when the range of the inverse cosecant is [,]. It is common to additionally define an inverse tangent function with two arguments , arctan ⁡ ( y , x ) . {\displaystyle \arctan(y,x).}