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- W113990105 abstract "Let X = {X(t), − ∞ < t < ∞} be a stationary stochastic process with univariate probability density f(x), covariance function R(t), and spectral density φ(λ). The nonparametric estimation of f, R, and φ on the basis of irregularly-spaced observations $$left{ {{text{X}}left( {{text{t}}_{text{k}} } right){text{,t}}_{text{k}} } right}_{{text{k = 1}}}^{text{n}}$$ is considered. The sampling schemes {tk} which allow the consistent estimation of f, R, and φ, as the sample size n → ∞, are identified and the asymptotic statistical properties of the corresponding estimates $${hat f_n}left( x right),{hat f_n}left( t right)$$ , and $$hat varphi _{text{n}} left( lambda right)$$ are presented." @default.
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- W113990105 date "1984-01-01" @default.
- W113990105 modified "2023-09-27" @default.
- W113990105 title "Spectral and Probability Density Estimation From Irregularly Observed Data" @default.
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- W113990105 doi "https://doi.org/10.1007/978-1-4684-9403-7_11" @default.
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