Efficiency of a Kernel Density Estimator Under an Autoregressive Dependence Model

DOI10.2307/2288344zbMath0553.62034OpenAlexW4230969059MaRDI QIDQ3347109

Jeffrey D. Hart

Publication date: 1984

Full work available at URL: https://doi.org/10.2307/2288344

zbMATH Keywords

independenceexponential distributioncharacteristic functionkernel density estimatormean integrated squared errornormaldependenceoptimal bandwidthCauchyfirst-order autoregressive modelstrictly stationary processFourier integral estimator

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Non-Markovian processes: estimation (62M09)

Related Items (12)

Asymptotic error rates of the W and Z statistics when the training observations are dependent ⋮ On bandwidth choice for density estimation with dependent data ⋮ OnL₁-consistency of kernel-type density estimator for stationary markov processes ⋮ Convergence rates in density estimation for data from infinite-order moving average processes ⋮ Integrated consistency of smoothed probability density estimators for stationary sequences ⋮ Some automated methods of smoothing time-dependent data ⋮ Density estimation for point processes ⋮ Exact risk approaches to smoothing parameter selection ⋮ Una clase de estimadores para los parametros de un proceso AR(1), obtenidos a partir de estimaciones no parametricas previas ⋮ On central and non-central limit theorems in density estimation for sequences of long-range dependence ⋮ Finite sample performance of density estimators from unequally spaced data ⋮ Optimal smoothing parameter of fourier series density estimates under an autoregressive dependence model

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