Semiparametric estimation for stationary processes whose spectra have an unknown pole

dc.creatorHidalgo, Javier
dc.date2005-08-17
dc.date.accessioned2026-07-07T08:07:10Z
dc.date.available2026-07-07T08:07:10Z
dc.descriptionWe consider the estimation of the location of the pole and memory parameter, λ^0 and α, respectively, of covariance stationary linear processes whose spectral density function f(λ) satisfies f(λ)\sim C| λ-λ^0| ^{-α} in a neighborhood of λ^0. We define a consistent estimator of λ^0 and derive its limit distribution Z_{λ^0}. As in related optimization problems, when the true parameter value can lie on the boundary of the parameter space, we show that Z_{λ^0} is distributed as a normal random variable when λ^0\in (0,π), whereas for λ^0=0 or π, Z_{λ^0} is a mixture of discrete and continuous random variables with weights equal to 1/2. More specifically, when λ^0=0, Z_{λ^0} is distributed as a normal random variable truncated at zero. Moreover, we describe and examine a two-step estimator of the memory parameter α, showing that neither its limit distribution nor its rate of convergence is affected by the estimation of λ^0. Thus, we reinforce and extend previous results with respect to the estimation of αwhen λ^0 is assumed to be known a priori. A small Monte Carlo study is included to illustrate the finite sample performance of our estimators.
dc.descriptionPublished at http://dx.doi.org/10.1214/009053605000000318 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/math/0508317
dc.identifierhttp://arxiv.org/abs/math/0508317
dc.identifierAnnals of Statistics 2005, Vol. 33, No. 4, 1843-1889
dc.identifierdoi:10.1214/009053605000000318
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130854
dc.subjectStatistics Theory
dc.subject62M15 (Primary) 62G05, 62G20 (Secondary)
dc.titleSemiparametric estimation for stationary processes whose spectra have an unknown pole
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