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This paper studies the estimation of a class of copula-based semiparametric stationary Markov models. These models are characterized by nonparametric marginal distributions and parametric copula functions, while the copulas capture all the scale-free temporal dependence of the processes. Simple estimators of the marginal distribution and the copula parameter are provided, and their asymptotic properties...
Asymptotic properties of the local Whittle estimator are studied under a model of fractional integration that provides a uniform representation of the data for any value of d. For d∈(-12,12), the estimator is shown to be consistent and asymptotically normally distributed. For d∈[-1,-12), the estimator converges either to the true parameter value or to zero, depending on the number of frequencies used...
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