This is effectively what OP does, but it is phrased there in terms of properties of the Li function, which makes it seem a little more exotic than thinking just in terms of differentiating power functions.
This is effectively what OP does, but it is phrased there in terms of properties of the Li function, which makes it seem a little more exotic than thinking just in terms of differentiating power functions.
a = sum_1 n^3 / 2^n
= sum_0 (n+1)^3 / 2^(n+1)
= (1/2) (1 + sum_1 (3n^2 + 3n + 1)/2^n)
b = sum_1 n^2 / 2^n
= (1/2) (1+ b + sum_1 (2n +1)/2^n)
c = sum_1 n / 2^n
= (1/2) (1+ c + sum_1 1 / 2^n)
d = sum_1 1 / 2^n
= sum_0 1 / 2^(n+1)
= (1/2) (1 + d)
= 1
d = 1 = 1
c = d + 1 = 1+1 = 2
b = d + 2c + 1 = 1+1+4 = 6
a = d + 3c + 3b + 1 = 1+1+6+18 = 26
In general, f_k = sum n^k/2^n
= (*k*th row of Pascal's triangle)•(f_0, ..., f_{k-1},1)
https://oeis.org/A000629Number of necklaces of partitions of n+1 labeled beads.
It happens in basic moment generating function manipulations (e.g., higher moments of random variables). Or from z-transforms in signal processing (z transforms of integrals or derivatives). And (a little less obvious, but still the same) from Fourier analysis.
The concept applies to any moment generating function, z-transform, whatever. It’s clearest for the geometric distribution, where the distribution itself has the geometric form (https://mathworld.wolfram.com/GeometricDistribution.html, around equation 6).
I agree that the Li function seems like a detour, but maybe it can make some of the manipulation easier?