SearcharxivSearch

arXiv · 1605.09052

The exact power law and Pascal pyramid

Abstract

Let $ω_0, ω_1,\ldots, ω_n$ be a full set of outcomes (letters, symbols) and let positive $p_i$, $i=0,\ldots,n$, be their probabilities ($\sum_{i=0}^n p_i=1$). Let us treat $ω_0$ as a stop symbol; it can occur in sequences of symbols (we call them words) only once, at the very end. The probability of a word is defined as the product of probabilities of its letters. We consider the list of all possible words sorted in the non-increasing order of their probabilities. Let $p(r)$ be the probability of the $r$th word in this list. We prove that if at least one of ratios $\log p_i/\log p_j$, $i,j\in\{ 1,\ldots,n\}$, is irrational, then the limit $\lim_{r\to\infty} p(r)/r^{1/γ}$ exists and differs from zero; here $γ$ is the root of the equation $\sum_{i=1}^n p_i^γ=1$. Some weaker results were established earlier. We are first to write an explicit formula for this limit constant at the power function; it can be expressed (rather easily) in terms of the entropy of the distribution~$(p_1^γ,\ldots,p_n^γ)$.

Explore related subjects

Keep this discovery

BibTeXRIS

Vladimir V. Bochkarev, Eduard Yu. Lerner. 2016-05-29. The exact power law and Pascal pyramid. https://doi.org/10.1155/2017%2F9143747

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Averaging principles for nonautonomous multiscale stochastic Burgers equations with reflection

In this paper, we study averaging principles for nonautonomous multiscale stochastic Burgers equations with reflection. First, we derive a general averaging principle applicable to such equations under minimal assumptions. Subsequently, since the coefficients of the obtained averaged equation still depend on the small scaling parameter $\e$, we impose either periodic or asymptotic conditions on the coefficients, thereby obtain two distinct averaged equations whose coefficients are independent of $\e$ and establish two averaging principles. Stopping times and Khasminskii's time discretization schemes play an important role. Finally, a concrete example is provided to illustrate the applicability and validity of the theoretical results.

math.PR

Spectral properties of Random Matrices

We give the theoretical foundations of random matrix theory through the definitions of a random matrix, a random probability measure and the corresponding empirical spectral distribution. The technical tool we use is the Stieltjes transform method through which we prove optimal convergence of the empirical spectral distribution of random sample covariance matrices to the deterministic Marchenko-Pastur distribution. We also give new results about the rigidity of the eigenvalues of this random sample covariance matrix and the rate of their convergence. We then define the Dyson equation method to prove new local laws about a random matrix model that interpolates between the Marchenko-Pastur distribution, the elliptical law and the circular law. Through our work these local laws can be considered universal.

math.PR

Moments approach for the elephant random walk

We discuss the method of moments for the one-dimensional elephant random walk (ERW). We first derive a differential recurrence relation for the characteristic function of the ERW, which yields a corresponding system of recurrence relations for its moments. We then obtain asymptotic approximations for the moments in each of the three parameter regimes of the ERW. Finally, by establishing the convergence of the moments and verifying the corresponding moment-determinacy conditions, we identify the limiting distributions of the ERW in each regime.

math.PR