Hadamard derivative

In mathematics, the Hadamard derivative is a concept of directional derivative for maps between Banach spaces. It is particularly suited for applications in stochastic programming and asymptotic statistics.[1]

Definition

A map φ : D E {\displaystyle \varphi :\mathbb {D} \to \mathbb {E} } between Banach spaces D {\displaystyle \mathbb {D} } and E {\displaystyle \mathbb {E} } is Hadamard-directionally differentiable[2] at θ D {\displaystyle \theta \in \mathbb {D} } in the direction h D {\displaystyle h\in \mathbb {D} } if there exists a map φ θ : D E {\displaystyle \varphi _{\theta }':\,\mathbb {D} \to \mathbb {E} } such that

φ ( θ + t n h n ) φ ( θ ) t n φ θ ( h ) {\displaystyle {\frac {\varphi (\theta +t_{n}h_{n})-\varphi (\theta )}{t_{n}}}\to \varphi _{\theta }'(h)}
for all sequences h n h {\displaystyle h_{n}\to h} and t n 0 {\displaystyle t_{n}\to 0} .

Note that this definition does not require continuity or linearity of the derivative with respect to the direction h {\displaystyle h} . Although continuity follows automatically from the definition, linearity does not.

Relation to other derivatives

  • If the Hadamard directional derivative exists, then the Gateaux derivative also exists and the two derivatives coincide.[2]
  • The Hadamard derivative is readily generalized for maps between Hausdorff topological vector spaces.

Applications

A version of functional delta method holds for Hadamard directionally differentiable maps. Namely, let X n {\displaystyle X_{n}} be a sequence of random elements in a Banach space D {\displaystyle \mathbb {D} } (equipped with Borel sigma-field) such that weak convergence τ n ( X n μ ) Z {\displaystyle \tau _{n}(X_{n}-\mu )\to Z} holds for some μ D {\displaystyle \mu \in \mathbb {D} } , some sequence of real numbers τ n {\displaystyle \tau _{n}\to \infty } and some random element Z D {\displaystyle Z\in \mathbb {D} } with values concentrated on a separable subset of D {\displaystyle \mathbb {D} } . Then for a measurable map φ : D E {\displaystyle \varphi :\mathbb {D} \to \mathbb {E} } that is Hadamard directionally differentiable at μ {\displaystyle \mu } we have τ n ( φ ( X n ) φ ( μ ) ) φ μ ( Z ) {\displaystyle \tau _{n}(\varphi (X_{n})-\varphi (\mu ))\to \varphi _{\mu }'(Z)} (where the weak convergence is with respect to Borel sigma-field on the Banach space E {\displaystyle \mathbb {E} } ).

This result has applications in optimal inference for wide range of econometric models, including models with partial identification and weak instruments.[3]

See also

  • Directional derivative – Instantaneous rate of change of the function
  • Fréchet derivative – Derivative defined on normed spaces - generalization of the total derivative
  • Gateaux derivative – Generalization of the concept of directional derivative
  • Generalizations of the derivative – Fundamental construction of differential calculus
  • Total derivative – Type of derivative in mathematics

References

  1. ^ Shapiro, Alexander (1990). "On concepts of directional differentiability". Journal of Optimization Theory and Applications. 66 (3): 477–487. CiteSeerX 10.1.1.298.9112. doi:10.1007/bf00940933. S2CID 120253580.
  2. ^ a b Shapiro, Alexander (1991). "Asymptotic analysis of stochastic programs". Annals of Operations Research. 30 (1): 169–186. doi:10.1007/bf02204815. S2CID 16157084.
  3. ^ Fang, Zheng; Santos, Andres (2014). "Inference on directionally differentiable functions". arXiv:1404.3763 [math.ST].
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