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Estimating invariant laws of linear processes by Ustatistics
"... Suppose we observe an invertible linear process with independent mean zero innovations, and with coefficients depending on a finitedimensional... ..."
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Cited by 11 (10 self)
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Suppose we observe an invertible linear process with independent mean zero innovations, and with coefficients depending on a finitedimensional...
Estimators for Models with Constraints Involving Unknown Parameters
"... Suppose we have independent observations from a distribution which we know to fulll a finitedimensional linear constraint involving an unknown finitedimensional parameter. We construct efficient estimators for finitedimensional functionals of the distribution. The estimators are obtained by first ..."
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Cited by 3 (3 self)
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Suppose we have independent observations from a distribution which we know to fulll a finitedimensional linear constraint involving an unknown finitedimensional parameter. We construct efficient estimators for finitedimensional functionals of the distribution. The estimators are obtained by first constructing an efficient estimator for the functional when the parameter is known, and then replacing the parameter by an efficient estimator. We consider in particular estimation of expectations.
Universität Bremen
"... We illustrate several recent results on efficient estimation for semiparametric time series models with two types of AR(1) models: having independent and centered innovations, and having general and conditionally centered innovations. We consider in particular estimation of the autoregression param ..."
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We illustrate several recent results on efficient estimation for semiparametric time series models with two types of AR(1) models: having independent and centered innovations, and having general and conditionally centered innovations. We consider in particular estimation of the autoregression parameter, the stationary distribution, the innovation distribution, and the stationary density. 1
Universität Bremen
"... Suppose we have independent observations from a distribution which we know to fulfill a finitedimensional linear constraint involving an unknown finitedimensional parameter. We construct efficient estimators for finitedimensional functionals of the distribution. The estimators are obtained by f ..."
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Suppose we have independent observations from a distribution which we know to fulfill a finitedimensional linear constraint involving an unknown finitedimensional parameter. We construct efficient estimators for finitedimensional functionals of the distribution. The estimators are obtained by first constructing an efficient estimator for the functional when the parameter is known, and then replacing the parameter by an efficient estimator. We consider in particular estimation of expectations. AMS 2000 subject classifications. Primary 62G05, 62G20. Key words and Phrases. Pluginestimator, estimating equation, method of mo
Estimators for alternating nonlinear autoregression
"... Suppose we observe a time series that alternates between different nonlinear autoregressive processes. We give conditions under which the model is locally asymptotically normal, derive a characterization of efficient estimators for differentiable functionals of the model, and use it to construct ef ..."
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Suppose we observe a time series that alternates between different nonlinear autoregressive processes. We give conditions under which the model is locally asymptotically normal, derive a characterization of efficient estimators for differentiable functionals of the model, and use it to construct efficient estimators for the autoregression parameters and the innovation distributions. Surprisingly, the estimators for the autoregression parameters can be improved if we know that the innovation densities are equal.