Titlebook: Nonparametric Curve Estimation from Time Series; Lázió Györfi,Wolfgang Härdle,Philippe Vieu Book 1989 Springer-Verlag Berlin Heidelberg 19

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书目名称Nonparametric Curve Estimation from Time Series影响因子(影响力)




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Lázió Györfi,Wolfgang Härdle,Pascal Sarda,Philippe Vieuau’s oeuvre, we recognize his critical disassociation from three theories of knowledge.. First, he is critical about a rationalist approach to overcome the confinements of human knowledge through the construction of knowledge of the external world out of indubitable principles possessed inherently b

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Lázió Györfi,Wolfgang Härdle,Pascal Sarda,Philippe Vieuau’s oeuvre, we recognize his critical disassociation from three theories of knowledge.. First, he is critical about a rationalist approach to overcome the confinements of human knowledge through the construction of knowledge of the external world out of indubitable principles possessed inherently b

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au’s oeuvre, we recognize his critical disassociation from three theories of knowledge.. First, he is critical about a rationalist approach to overcome the confinements of human knowledge through the construction of knowledge of the external world out of indubitable principles possessed inherently b

前面

Introduction.,onomics. One wants to know whether some regularly observed economic indicator follows certain regularities. Once a regularity is detected, prediction and also speculation can be based on it. This is probably the most striking example that most people are aware of.

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Dependent Samples,) be the σ-algebra generated by {Z., n≤i≤m}. In this chapter we summarize some dependence structures and some basic results which are used in the sequel. If we say that (Z.). is stationary, then it means strict stationarity. For the definition of ergodicity we refer to Ibragimov and Linnik (1971).

物质

Regression Estimation and Time Series Analysis,on is in particular satisfied when the process (X., Y.) is stationary, but this assumption will not be necessary for a lot of results presented here. Here r has to be understood as an arbitrary element of the equivalence class of functions defined by (3.1.1). The knowledge of r is helpful in constru

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Density Estimation,le X., X., …, X.. denotes the density estimate. Here f is a measurable function of its arguments and f. is itself a density, i.e. for each x∈ℝ. f. (x)≥O and ∫f. (x)λ(dx)=l. (In the sequel ∫g will denote the integral of g over ℝ. with respect to the Lebesgue measure λ.)