Math 2.0

statement proposition

Derivative as a little-o approximation

Statement

Let VV and WW be normed vector spaces over R\mathbb{R}, let U⊆VU \subseteq V be open, and let f ⁣:U→Wf \colon U \to W. Let x∈Ux \in U, and let A ⁣:V→WA \colon V \to W be a bounded linear map. Then AA is the Fréchet derivative of ff at xx if and only if f(x+h)=f(x)+Ah+r(h),where r(h)=o(∥h∥) as h→0.f(x + h) = f(x) + A h + r(h), \qquad \text{where } r(h) = o(\|h\|) \text{ as } h \to 0. Here r(h)=o(∥h∥)r(h) = o(\|h\|) means that for each ε>0\varepsilon > 0 there is a δ>0\delta > 0 such that ∥r(h)∥≤ε∥h∥\|r(h)\| \le \varepsilon \|h\| for each hh with ∥h∥<δ\|h\| < \delta and x+h∈Ux + h \in U.

Remarks

The remainder r(h)r(h) is defined by the equation, so the statement says that the error of the linear approximation tends to 00 faster than ∥h∥\|h\|. The little-o form includes h=0h = 0, where r(0)=0r(0) = 0. This is why it uses ≤\le and does not divide by ∥h∥\|h\|. This form is often the most convenient one for proofs, for example of the chain rule.

Explanations

L1 human

The equation splits f(x+h)f(x + h) into three parts: the value at xx, a linear part in hh, and an error. The derivative condition says only that the error is tiny compared with the step: halving the step more than halves the error.

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Sources

  1. Web https://en.wikipedia.org/wiki/Fr%C3%A9chet_derivative, Definition