TY - JOUR
T1 - Renewal Model for Dependent Binary Sequences
AU - Zamparo, Marco
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022/4
Y1 - 2022/4
N2 - We suggest to construct infinite stochastic binary sequences by associating one of the two symbols of the sequence with the renewal times of an underlying renewal process. Focusing on stationary binary sequences corresponding to delayed renewal processes, we investigate correlations and the ability of the model to implement a prescribed autocovariance structure, showing that a large variety of subexponential decay of correlations can be accounted for. In particular, robustness and efficiency of the method are tested by generating binary sequences with polynomial and stretched-exponential decay of correlations. Moreover, to justify the maximum entropy principle for model selection, an asymptotic equipartition property for typical sequences that naturally leads to the Shannon entropy of the waiting time distribution is demonstrated. To support the comparison of the theory with data, a law of large numbers and a central limit theorem are established for the time average of general observables.
AB - We suggest to construct infinite stochastic binary sequences by associating one of the two symbols of the sequence with the renewal times of an underlying renewal process. Focusing on stationary binary sequences corresponding to delayed renewal processes, we investigate correlations and the ability of the model to implement a prescribed autocovariance structure, showing that a large variety of subexponential decay of correlations can be accounted for. In particular, robustness and efficiency of the method are tested by generating binary sequences with polynomial and stretched-exponential decay of correlations. Moreover, to justify the maximum entropy principle for model selection, an asymptotic equipartition property for typical sequences that naturally leads to the Shannon entropy of the waiting time distribution is demonstrated. To support the comparison of the theory with data, a law of large numbers and a central limit theorem are established for the time average of general observables.
KW - Central limit theorem
KW - Dependent binary data
KW - Inverse problems
KW - Law of large numbers
KW - Maximum entropy principle
KW - Stationary binary sequences
UR - http://www.scopus.com/inward/record.url?scp=85125334816&partnerID=8YFLogxK
U2 - 10.1007/s10955-022-02893-8
DO - 10.1007/s10955-022-02893-8
M3 - Article
SN - 0022-4715
VL - 187
JO - Journal of Statistical Physics
JF - Journal of Statistical Physics
IS - 1
M1 - 5
ER -