Additive time series: The kernel integration method
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Publication:1856562
zbMath1008.62039MaRDI QIDQ1856562
Philippe Vieu, Pascal Sarda, Ch. Camlong-Viot
Publication date: 10 February 2003
Published in: Mathematical Methods of Statistics (Search for Journal in Brave)
additive modelscurse of dimensionalitytime series predictionnonparametric multivariate regressionabsolutely regular sequenceskernel integration estimators
Inference from stochastic processes and prediction (62M20) Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)
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Uniform convergence of the estimator of an additive regression function under random censorship ⋮ Asymptotic normality for the wavelets estimator of the additive regression components ⋮ Mean square convergence for estimators of additive regression under random censorship ⋮ Strong consistency of the internal estimator of nonparametric regression with dependent data ⋮ Additive Regression Model for Continuous Time Processes ⋮ Asymptotic normality of the additive regression components for continuous time processes ⋮ Law of iterated logarithm for additive regression model components. ⋮ An efficient marginal integration estimator of a semiparametric additive modelling
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