injectivity implies that null space is {0}
Last edited: August 8, 2025inner product
Last edited: August 8, 2025constituents
- \(V\) a vector space
- \((u,v)\), an ordered pair of vectors in \(V\) (its not commutative!)
requirements
We define \(\langle u, v \rangle \in \mathbb{F}\) as the inner product of \((u,v)\) in that order!. It carries the following properties:
- positivity: \(\langle v, v\rangle \geq 0, \forall v \in V\)
- definiteness: \(\langle v, v\rangle = 0\) IFF \(v = 0\)
- additivity in the first slot: \(\langle u+v, w\rangle = \langle u, w \rangle + \langle v, w \rangle\)
- homogeneity in the first slot: \(\langle \lambda u, v \rangle = \lambda \langle u, v \rangle\)
- conjugate symmetry: \(\langle u,v \rangle = \overline{\langle v,u \rangle}\)
additional information
Inner Product Space
An Inner Product Space is a vector space with a well-defined inner product. For instance, \(\mathbb{F}^{n}\) has the canonical inner product named Euclidean Inner Product (see below, a.k.a. dot product for reals). The existence of such a well-defined inner product makes \(\mathbb{F}^{n}\) an Inner Product Space.
integer
Last edited: August 8, 2025an integer (\(\mathbb{Z}\)) is the natural numbers, zero, and negative numbers: …,-4,-3,-2,-1,0,1,2,2,3
representing integers
- what are the limitations of computational arithmetic
- how to perform efficient arithmetic
- how to encode data more compactly and efficiently
See also computer number system
integrating factor
Last edited: August 8, 2025The integrating factor \(\rho(x)\) is a value that helps undo the product rule. For which:
\begin{equation} log(\rho(x)) = \int P(x)dx \end{equation}
for some function \(P(x)\).
Separating the \(\rho(x)\) out, we have therefore:
\begin{equation} e^{\int P dx} = \rho(x) \end{equation}
Why is this helpful and undoes the product rule? This is because of a very interesting property of how \(\rho(x)\) behaves.
Inter-Temporal Choice
Last edited: August 8, 2025Goal
We are going to solve the inter-temporal choice problem, for ten time stamps, and perform some numerical optimization of the results
Main Methods
We do this by solving backwards. We will create a variable \(k\) to measure asset, and \(k_{t}\) the remaining asset at time \(t\).
Let us first declare the function for power utility. \(k\) is our asset holding, \(\gamma\) our relative margin of risk, and \(U\) the power utility.
