Wavelets for time series analysis - a survey and new results
Variance function estimation via model selection
The problem of estimating an unknown variance function in a random design Gaussian heteroscedastic regression model is considered. Both the regression function and the logarithm of the variance function are modelled by piecewise polynomials. A finite collection of such parametric models based on a family of partitions of support of an explanatory variable is studied. Penalized model selection criteria as well as post-model-selection estimates are introduced based on Maximum Likelihood (ML) and Restricted...
On asymptotic minimaxity of the adaptative kernel estimate of a density function
On construction of confidence intervals for a mean of dependent data
In the report, the performance of several methods of constructing confidence intervals for a mean of stationary sequence is investigated using extensive simulation study. The studied approaches are sample reuse block methods which do not resort to bootstrap. It turns out that the performance of some known methods strongly depends on a model under consideration and on whether a two-sided or one-sided interval is used. Among the methods studied, the block method based on weak convergence result by...
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Artykuł Ryszarda Zielińskiego, Przedział ufności dla frakcji, opubliko-wany w MATEMATYCE STOSOWANEJ, tom 10/51 2009, wymaga ko-mentarza oraz zmusza nas do postawienia kilku pytań.
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