Displaying similar documents to “The Bayes approach in multiple autoregressive series”

Statistical analysis of periodic autoregression

Jiří Anděl (1983)

Aplikace matematiky

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Methods for estimating parameters and testing hypotheses in a periodic autoregression are investigated in the paper. The parameters of the model are supposed to be random variables with a vague prior density. The innovation process can have either constant or periodically changing variances. Theoretical results are demonstrated on two simulated series and on two sets of real data.

Periodic autoregression with exogenous variables and periodic variances

Jiří Anděl (1989)

Aplikace matematiky

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The periodic autoregressive process with non-vanishing mean and with exogenous variables is investigated in the paper. It is assumed that the model has also periodic variances. The statistical analysis is based on the Bayes approach with a vague prior density. Estimators of the parameters and asymptotic tests of hypotheses are derived.