2011/08/21 by Elvira Di Nardo, E. Di Nardo, D. Senato · 1 citation
Computer Science · Mathematics · #Advanced Combinatorial Mathematics #Algebra over a field #Algorithm #Algorithms and Data Compression #Artificial intelligence #Class (philosophy) #Computer science #Discrete mathematics #Mathematical analysis #Mathematics #Polynomial #Pure mathematics #Representation (politics) #State (computer science) #Symbol (formal) #Variable (mathematics) #math.CO #semigroups and automata theory
paper · pdf · doi:10.1016/j.jspi.2011.07.022
published in Journal of Statistical Planning and Inference 142(2), 423-429 (Elsevier BV) · arXiv admin note: text overlap with arXiv:0810.3554
openalex publication_date 2011/08/21 · arxiv created 2021/01/21 · arxiv updated 2021/01/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
A symbolic method for solving linear recurrences of combinatorial and statistical interest is introduced. This method essentially relies on a representation of polynomial sequences as moments of a symbol that looks as the framework of a random variable with no reference to any probability space. We give several examples of applications and state an explicit form for the class of linear recurrences involving Sheffer sequences satisfying a special initial condition. The results here presented can be easily implemented in a symbolic software.