Recurrence relations and Benford’s law
نویسندگان
چکیده
منابع مشابه
Generalizing Benfords Law Using Power Laws: Application to Integer Sequences
A simple method to derive parametric analytical extensions of Benfords law for first digits of numerical data is proposed. Two generalized Benford distributions are considered, namely the two-sided power Benford (TSPB) distribution, which has been introduced in Hürlimann(2003), and the new Pareto Benford (PB) distribution. Based on the minimum chisquare estimators, the fitting capabilities of ...
متن کاملRecurrence relations and fast algorithms
We construct fast algorithms for evaluating transforms associated with families of functions which satisfy recurrence relations. These include algorithms both for computing the coefficients in linear combinations of the functions, given the values of these linear combinations at certain points, and, vice versa, for evaluating such linear combinations at those points, given the coefficients in t...
متن کامل( Probabilistic ) Recurrence Relations
The performance attributes of a broad class of randomised algorithms can be described by a recurrence relation of the form T(x) = a(x)+T(H(x)), where a is a function and H(x) is a random variable. For instance, T(x) may describe the running time of such an algorithm on a problem of size x. Then T(x) is a random variable, whose distribution depends on the distribution of H(x). To give high proba...
متن کاملRECURRENCE RELATIONS , FRACTALS , AND CHAOS 1 Recurrence Relations , Fractals , and Chaos : Implications for Analyzing Gene Structure
The " chaos game " is a well-known algorithm by which one may construct a pictorial representation of an iterative process. The resulting sets are known as fractals and can be mathematically characterized by measures of dimension as well as by their associated recurrence relations. Using the chaos game algorithm, is it possible to derive meaningful structure out of our own genetic encoding, and...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistical Methods & Applications
سال: 2020
ISSN: 1618-2510,1613-981X
DOI: 10.1007/s10260-020-00547-1