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Fokianos, Konstantinos; Tjøstheim, Dag

Nonlinear Poisson autoregression. (English) Zbl 1253.62058

Ann. Inst. Stat. Math. 64, No. 6, 1205-1225 (2012).
Summary: We study statistical properties of a class of nonlinear models for regression analysis of count time series. Under mild conditions, it is shown that a perturbed version of the model is geometrically ergodic and possesses moments of any order. This result turns out to be instrumental on deriving large sample properties of the maximum likelihood estimators of the regression parameters. The theory is illustrated with examples.

Cited in 1 Review
Cited in 41 Documents

MSC:

62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62J02 General nonlinear regression
62F12 Asymptotic properties of parametric estimators
65C60 Computational problems in statistics (MSC2010)

Keywords:

geometric ergodicity; link function; maximum likelihood estimation; perturbation; smooth transition models

Software:

Fahrmeir
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Full Text: DOI

References:

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