Thanks, David. I suspect I have something wrong with my preamble because [t] is just getting typeset as part of the first term [t]y_{1}a_{1}. Will try and figure it out!
(I'd like to maintain the matrix and would prefer not to break it up into several lines which is what has often been suggested in my searches for a solution)
This is a bit of a strange one and I don't think it deserves its own post on main but does anybody think this pdf is generated with (La)TeX? https://www.ardent-tool.com/CPU/docs/AMD/anatomy/misc/articles/r9043.pdf
@ThomasFinley I believe it's Vector Calculus, Linear Algebra, and Differential Forms: A Unified Approach Textbook by Barbara Burke Hubbard and John H. Hubbard
In mathematics, a measurable space or Borel space is a basic object in measure theory. It consists of a set and a σ-algebra, which defines the subsets that will be measured.
== Definition ==
Consider a set
X
{\displaystyle X}
and a σ-algebra
F
{\displaystyle {\mathcal {F}}}
on
X
.
{\displaystyle X.}
Then the tuple
(
X
,
F...
(because you may be dealing with a function from a measurable space into another general measurable space that might not be $(\mathbb{R}^{n}, \mathcal{B}(\mathbb{R}^{n})$)
According to Wikipedia | We have the following chain of strict inclusions for functions over a closed and bounded non-trivial interval of the real line: Continuously differentiable ⊂ Lipschitz continuous ⊂ α-Hölder continuous
From a structural point of view, I wholeheartedly agree with OP. It's nice to know the hierarchy of objects and leaving out something so basic (/fundamental/simple) always leaves a sour taste for me.
Hey everyone, I have a few questions about the building blocks of random variables and their probability distributions. Is anybody here to bounce some ideas off?