This paper gives a brief overview of the nonparametric techniques that are useful for
financial econometric problems. The problems include estimation and inference for …

Master linear regression techniques with a new edition of a classic text Reviews of the
Second Edition:" I found it enjoyable reading and so full of interesting material that even the …

This package includes both Mathematical Statistics: Basic Ideas and Selected Topics,
Volume I, Second Edition, as well as Mathematical Statistics: Basic Ideas and Selected …

Semiparametric regression is concerned with the flexible incorporation of non-linear
functional relationships in regression analyses. Any application area that benefits from …

Amongmanyexcitingdevelopmentsinstatistic…, nonlineartimeseriesanddata-
analyticnonparametricmethodshavegreatly advanced along seemingly unrelated paths. In …

Separation of signal from noise is the most fundamental problem in data analysis, and arises
in many fields, for example, signal processing, econometrics, acturial science, and …

Conditional heteroscedasticity has often been used in modelling and understanding the
variability of statistical data. Under a general set-up which includes nonlinear time series …

2.1 Background Exhaustive empirical surveys have shown that, almost without exception,
macroparasites (parasitic helminths and arthropods) are aggregated across their host …

Adaptation over different procedures is of practical importance. Different procedures perform
well under different conditions. In many practical situations, it is rather hard to assess which …

The paper studies spline fitting with a roughness penalty that adapts to spatial heterogeneity
in the regression function. The estimates are pth degree piecewise polynomials with p− 1 …