Data-Driven Efficient Estimation of the Spectral Density

DOI10.2307/2670126zbMath0918.62071OpenAlexW4240576988MaRDI QIDQ4216971

Sam Efromovich

Publication date: 13 December 1998

Full work available at URL: https://doi.org/10.2307/2670126

zbMATH Keywords

minimaxasymptoticmean integrated squared erroradaptationsmall sample sizesinsulin secretionautoregressive moving average process

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Inference from stochastic processes and spectral analysis (62M15)

Related Items (9)

Nonparametric estimation of the spectral density of amplitude-modulated time series with missing observations ⋮ Autoregressive process modeling via the Lasso procedure ⋮ Testing Kendall's τ for a large class of dependent sequences ⋮ On Two‐Stage Estimation of the Spectral Density with Assigned Risk in Presence of Missing Data ⋮ Missing not at random and the nonparametric estimation of the spectral density ⋮ EFFICIENT NON‐PARAMETRIC ESTIMATION OF THE SPECTRAL DENSITY IN THE PRESENCE OF MISSING OBSERVATIONS ⋮ Estimation of the Spectral Density with Assigned Risk ⋮ On sequential spectral analysis of amplitude-modulated time series ⋮ Nonasymptotic bounds for autoregressive time series modeling.

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