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Sieve Bootstrap With Variable-Length Markov Chains for Stationary Categorical Time Series

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  • Buhlmann P.

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  • Buhlmann P., 2002. "Sieve Bootstrap With Variable-Length Markov Chains for Stationary Categorical Time Series," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 443-471, June.
    • Handle: RePEc:bes:jnlasa:v:97:y:2002:m:june:p:443-471
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    Cited by:

    1. Simionescu, Mihaela, 2014. "New Strategies to Improve the Accuracy of Predictions based on Monte Carlo and Bootstrap Simulations: An Application to Bulgarian and Romanian Inflation || Nuevas estrategias para mejorar la exactitud," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 18(1), pages 112-129, December.
    2. Cerqueti, Roy & Falbo, Paolo & Pelizzari, Cristian, 2017. "Relevant states and memory in Markov chain bootstrapping and simulation," European Journal of Operational Research, Elsevier, vol. 256(1), pages 163-177.

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