complements the periodogram, a widely used tool for period estimation. The CV method is computationally simple and implicitly … spaced time points. The basic idea is to borrow information from other correlated sequences to improve estimation of the …

Nonparametric methods for the estimation of the Levy density of a Levy process X are developed. Estimators that can be …. By providing lower bounds for the minimaxrisk of estimation over Besov Levy densities, our estimators are shownto achieve …

reality these densities are usually not available, and parametric or non-parametric estimation of the densities becomes … critically needed.In parametric estimation one assumes that the density f underlying the data yi where i varies from 1 to n … members f(•;θ) is close to f.In nonparametric density estimation no parametric assumptions about f are made and one assumes …

The estimation of conditional probability distribution functions (PDFs) in a kernel nonparametric framework has … nonparametric kernel estimation of PDF with a binary choice variable and both continuous and discrete explanatory variables. Second …

Spatial characterization of non-Gaussian attributes in earth sciences and engineering commonly requires the estimation … the estimation variance of probability estimates is performed, as additional data are successively included into the … estimation process. In addition, the approach leads to an efficient nonparametric simulation algorithm for non-Gaussian random …

estimation, using local quadratic smoothing of the data, of components of these models is discussed and employed to help to check …