Abstract
Nonnegative MA(1) and MA(2) models are investigated in the paper. A new method for estimating their parameters is proposed. It is proved that the estimators are strongly consistent. Small-sample properties are demonstrated on a simulation study. Real data on biological oxygen demand are analyzed by the new method.
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References
Anděl J., On AR(1) processes with exponential white noise, Commun. Statist.-Theory Meth. 17 (1988), 1481–1495.
Anděl J., Non-negative autoregressive processes, Time Ser. Anal. 10 (1989), 1–11.
Anděl M., Non-negative linear processes, Api. mat. 36 (1991), 277–283.
Bell C. B. and Smith E. P., Inference for non-negative autoregressive schemes, Commun. Statist.-Theory Meth. 15 (1986), 2267–2293.
Box G. E. P., Jenkins G. M., Time Series Analysis. Forecasting and control, Holden Day, San Francisco, 1970.
Turkman M. A. A., Bayesian analysis of an autoregressive process with exponential white noise, Statistics 21 (1990), 601–608.
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© 1994 Springer-Verlag Berlin Heidelberg
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Anděl, J. (1994). Nonnegative Moving-Average Models. In: Mandl, P., Hušková, M. (eds) Asymptotic Statistics. Contributions to Statistics. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57984-4_12
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DOI: https://doi.org/10.1007/978-3-642-57984-4_12
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-0770-7
Online ISBN: 978-3-642-57984-4
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