Given a function of real numbers f(x), I can create approximations to arbitrary precision using Taylor polynomials.
Is there something equivalent in the discrete case when I have a sequence of integers that I want to approximate to arbitrary precision.
One reason for approximating a real function by Taylor polynomials is to use properties of polynomials (and the real numbers) to estimate the function at an unknown value. In order for this to be useful, f has to behave consistently with the assumptions needed to use the approximations. In particular, f has to be a certain kind of continuous (normal or Hoelder, say). Or one assumes f is differentiable, and then uses the derivative of the approximation. Or one assumes f is bounded on an interval, but is increasing and larger than the input outside the interval. The key thing is to choose a property that you want f to have or believe it to have, then you use the tools and components which support that property or set of properties.
One often has something similar with sequences. As two examples, there is the one-complexity of an integer which has somewhat erratic behaviour, but has logarithmic lower and upper bounds, and whose value at certain integers is known exactly, and at other integers there are quickly computed approximations with provably small error. Another function is the sequence of prime gaps, which grows less slowly, more erratically, and on which much computation has been done, but approximations are poor still. We can say there are lots of n for which $ p_{n+1} - p_n $ is equal to 30, and even have an idea of how many, but we can't tell you which n have that value unless n is less than 10^19, and even then there is the issue of computational energy and retrieval energy involved.
So yes, there are methods, but you have to use a property that your sequence has or that you believe it has. Until I know of those properties, I can't tell you a wise way to proceed.
Gerhard "Wisdom Comes Only After Experiencing" Paseman, 2018.07.23.
