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  2. Chain rule - Wikipedia

    en.wikipedia.org/wiki/Chain_rule

    In this situation, the chain rule represents the fact that the derivative of f ∘ g is the composite of the derivative of f and the derivative of g. This theorem is an immediate consequence of the higher dimensional chain rule given above, and it has exactly the same formula. The chain rule is also valid for Fréchet derivatives in Banach spaces.

  3. Chain rule (probability) - Wikipedia

    en.wikipedia.org/wiki/Chain_rule_(probability)

    In probability theory, the chain rule [1] (also called the general product rule [2] [3]) describes how to calculate the probability of the intersection of, not necessarily independent, events or the joint distribution of random variables respectively, using conditional probabilities.

  4. Faà di Bruno's formula - Wikipedia

    en.wikipedia.org/wiki/Faà_di_Bruno's_formula

    Faà di Bruno's formula is an identity in mathematics generalizing the chain rule to higher derivatives. It is named after Francesco Faà di Bruno ( 1855 , 1857 ), although he was not the first to state or prove the formula.

  5. Total derivative - Wikipedia

    en.wikipedia.org/wiki/Total_derivative

    The chain rule has a particularly elegant statement in terms of total derivatives. It says that, for two functions f {\displaystyle f} and g {\displaystyle g} , the total derivative of the composite function f ∘ g {\displaystyle f\circ g} at a {\displaystyle a} satisfies

  6. Triple product rule - Wikipedia

    en.wikipedia.org/wiki/Triple_product_rule

    Suppose a function f(x, y, z) = 0, where x, y, and z are functions of each other. Write the total differentials of the variables = + = + Substitute dy into dx = [() + ()] + By using the chain rule one can show the coefficient of dx on the right hand side is equal to one, thus the coefficient of dz must be zero () + = Subtracting the second term and multiplying by its inverse gives the triple ...

  7. Related rates - Wikipedia

    en.wikipedia.org/wiki/Related_rates

    The chain rule can be used to find whether they are getting closer or further apart. For example, one can consider the kinematics problem where one vehicle is heading West toward an intersection at 80 miles per hour while another is heading North away from the intersection at 60 miles per hour.

  8. Conditional entropy - Wikipedia

    en.wikipedia.org/wiki/Conditional_entropy

    As in the discrete case there is a chain rule for differential entropy: (|) = (,) [3]: 253 Notice however that this rule may not be true if the involved differential entropies do not exist or are infinite.

  9. Thermodynamic equations - Wikipedia

    en.wikipedia.org/wiki/Thermodynamic_equations

    Just as with the internal energy version of the fundamental equation, the chain rule can be used on the above equations to find k+2 equations of state with respect to the particular potential. If Φ is a thermodynamic potential, then the fundamental equation may be expressed as: