Hello Please tell that how the given process i:e the general random walk tends to a normal distribution after large number of time priods. Also,how do we then estimate the parameters of the distribution?
I think you mean the distribution of X(n) is approximately normal for large n. If X is a RW, then: X(n) = Z(1) + Z(2) + ... Z(n) where Z is white noise, ie the Z's are IID RVs. By the Central Limit Theorem, the distribution of a sum of n IID RVs is approx normal with mean n*mu and variance n*sigma^2, provided n is large. Here mu = E(Z) and sigma^2 = var(Z).
