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A model and application of binary random sequence with probabilities depending on history
Kybernetika, Tome 60 (2024) no. 1, pp. 110-124
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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.
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.
DOI : 10.14736/kyb-2024-1-0110
Classification : 60G50, 62J12, 62N02
Keywords: recurrent events; discrete time process; binary sequence; varying probabilities; logistic regression; time-dependent parameters 
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Volf, Petr; Kouřim, Tomáš. A model and application of binary random sequence with probabilities depending on history. Kybernetika, Tome 60 (2024) no. 1, pp. 110-124. doi: 10.14736/kyb-2024-1-0110

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