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An algorithm for prior elicitation in dynamic Bayesian models for proportions with the logit link function. (English) Zbl 1411.62262

Summary: The elicitation of hyperparameters at time \(t\) in dynamic Bayesian models for proportions is performed by solving a nonlinear system. This paper presents an algorithm to solve this system when the logit function is used. If the initial conditions are satisfied, it is guaranteed that the algorithm converges to the solution. The performance of some dynamic models was compared using the standard method and the new method presented here, using simulated data and the monthly series of deaths from tuberculosis sequelae in the state of São Paulo, Brazil.

MSC:

62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62J12 Generalized linear models (logistic models)
62P10 Applications of statistics to biology and medical sciences; meta analysis

Software:

Forecast; forecast; R
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References:

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