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The non-parametric estimation of the growth curve has been extensively studied in both stationary and some nonstationary particular situations. In this work, we consider the statistical problem of estimating the average growth curve for a fixed design model with nonstationary error process. The nonstationarity considered here is of a general form, and this(More)
The optimal sampling problem for the estimation of an integral, based on observations, with random and correlated measurement errors is treated. Considering the effect of the quantization of errors, we determine the optimal design, which is constructed by utilizing stochastic algorithms. The efficiency of the Genetic Algorithm is confirmed by comparison(More)
We propose an asymptotically unbiased and consistent estimate of the bispectrum of a stationary continuous-time process X = {X(t)} t∈R. The estimate is constructed from observations obtained by a random sampling of the time by {X(τ k)} k∈Z , where {τ k } k∈Z is a sequence of real random variables, generated from a Poisson counting process. Moreover, we(More)
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