Do either of $c\cdot I_n-A$ or $A-c\cdot I_n$ have a name? Let $A$ be an $n\times n$ matrix and let $c$ be a scalar. The matrices $c\cdot I_n-A$ and $A-c\cdot I_n$ are used to say interesting things about $A$. Do either of $c\cdot I_n-A$ and $A-c\cdot I_n$ have a name?
It seems like calling $A-c\cdot I_n$ something like the "shift of $A$ by a factor of $c$" makes sense, but "shift matrices" usually refer to binary matrices whose only nonzero entries are either on the superdiagonal or subdiagonal.
I suppose it's also worth asking if either of $c\cdot I-T$ or $T-c\cdot I$ have a name if $T:V\to V$ is a linear endomorphism of a vector space $V$ and $I:V\to V$ is the identity.
 A: I am not aware of any special name for an operator or matrix of the form $\lambda I - T$ (or $cI - A$) in either linear algebra or functional analysis.  However, some possibilities are


*

*an inverse of the resolvent,

*a pseudoinverse of the resolvent, or

*a pre-resolvent.


All three of these are meant to capture the the notion that $cI - A$ has a relation to the resolvent operator, though the exact nature of that relation is a little delicate.  More context is provided below.

Given that endomorphisms of vector spaces are mentioned, it may be that much of the following is redundant for the asker.[1]  However, I think that the following discussion helps to justify the terminology suggested above.
In functional analysis, if $T$ is a bounded linear operator on a Banach space (a topological vector space possessing a complete norm) and $\lambda \in \mathbb{C}$, then the resolvent operator (corresponding to $T$ at $\lambda$) is defined to be
$$ R_{\lambda} := (\lambda I - T)^{-1}, $$
where $I$ is the identity operator.
The resolvent operator plays a special role in functional analysis:  the resolvent set of $T$ consists of all of the values of $\lambda$ such that $R_{\lambda}$ is a bounded linear operator (e.g. it exists and is bounded), while the spectrum of $T$ consists of all other values of $\lambda$.  In the case that $T : \mathbb{R}^n \to \mathbb{R}^n$, then $T$ may be represented by an $n\times n$ matrix, and the spectrum of $T$ will correspond to the set of eigenvalues.  The Wikipedia article on spectral theory offers a reasonable summary.

[1] And now that I have checked out the asker's profile, I am reasonably certain that the context is redundant.  However, it might be useful to others. ;)
A: It is a specific type of linear matrix pencil.
