A model and application of binary random sequence with probabilities depending on history

Petr Volf; Tomáš Kouřim

Kybernetika (2024)

  • Issue: 1, page 110-124
  • ISSN: 0023-5954

Abstract

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This paper presents a model of binary random sequence with probabilities depending on previous sequence values as well as on a set of covariates. Both these dependencies are expressed via the logistic regression model, such a choice enables an easy and reliable model parameters estimation. Further, a model with time-depending parameters is considered and method of solution proposed. The main objective is then the application dealing with both artificial and real data cases, illustrating the method of model evaluation and its use.

How to cite

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Volf, Petr, and Kouřim, Tomáš. "A model and application of binary random sequence with probabilities depending on history." Kybernetika (2024): 110-124. <http://eudml.org/doc/299385>.

@article{Volf2024,
abstract = {This paper presents a model of binary random sequence with probabilities depending on previous sequence values as well as on a set of covariates. Both these dependencies are expressed via the logistic regression model, such a choice enables an easy and reliable model parameters estimation. Further, a model with time-depending parameters is considered and method of solution proposed. The main objective is then the application dealing with both artificial and real data cases, illustrating the method of model evaluation and its use.},
author = {Volf, Petr, Kouřim, Tomáš},
journal = {Kybernetika},
keywords = {recurrent events; discrete time process; binary sequence; varying probabilities; logistic regression; time-dependent parameters},
language = {eng},
number = {1},
pages = {110-124},
publisher = {Institute of Information Theory and Automation AS CR},
title = {A model and application of binary random sequence with probabilities depending on history},
url = {http://eudml.org/doc/299385},
year = {2024},
}

TY - JOUR
AU - Volf, Petr
AU - Kouřim, Tomáš
TI - A model and application of binary random sequence with probabilities depending on history
JO - Kybernetika
PY - 2024
PB - Institute of Information Theory and Automation AS CR
IS - 1
SP - 110
EP - 124
AB - This paper presents a model of binary random sequence with probabilities depending on previous sequence values as well as on a set of covariates. Both these dependencies are expressed via the logistic regression model, such a choice enables an easy and reliable model parameters estimation. Further, a model with time-depending parameters is considered and method of solution proposed. The main objective is then the application dealing with both artificial and real data cases, illustrating the method of model evaluation and its use.
LA - eng
KW - recurrent events; discrete time process; binary sequence; varying probabilities; logistic regression; time-dependent parameters
UR - http://eudml.org/doc/299385
ER -

References

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  5. Kouřim, T., Random walks with memory applied to grand slam tennis matches modeling., In: Proc. MathSport International 2019 Conference (e-book). Propobos Publications 2019, pp. 220-227. 
  6. Kouřim, T., Volf, P., , Appl. Math.65 (2020), 271-286. MR4114252DOI
  7. Möller, T. A., , Stoch. Models 32 (2016), 77-98. MR3457122DOI
  8. Murphy, S. A., Sen, P. K., , Stoch. Proc. Appl. 39 (1991), 153-180. MR1135092DOI
  9. Volf, P., Kouřim, T., , Commun. Statist. - Theory and Methods 52 (2023), 5173-5186. MR4597932DOI
  10. Wei, L. T., Lin, D. Y., Weissfeld, L., , J. Amer. Statist. Assoc. 84 (1989), 1065-1073. MR1134494DOI
  11. Weiss, Ch. H., An Introduction to Discrete Valued Time Series., Wiley, New York 2018. 
  12. Winkelmann, R., Econometric Analysis of Count Data., Springer, Berlin 2008. MR2148271

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