Titlebook: Nonparametric Curve Estimation from Time Series; Lázió Gy?rfi,Wolfgang H?rdle,Philippe Vieu Book 1989 Springer-Verlag Berlin Heidelberg 19

戰(zhàn)勝

oncologist

Book 1989jects or topics. No single volume can survey the whole field in any depth and what follows is, therefore, a series of chapters on selected topics. The topics were selected by us, the editors, because of their immediate relevance to the plastics industry. When one considers the advancements of the pl

面包屑

ARK

Distribution and Hazard Functions Estimation,Let X be a random variable valued in ?., d ≥ 1, with distribution F and density f. We investigate, from a sample X......X. drawn from f, the estimation of the hazard function, also called failure rate, defined for any x in ?., F(x)

劇本

How to Select the Smoothing Parameter?,From the results given in the previous sections it appeared that the bandwidth h played a dominant role in the behaviour of kernel estimates for regression, density or hazard function estimation.

琺瑯

effrontery

https://doi.org/10.1007/978-1-4612-3686-3Processing; Scope; Volume; behavior; boundary element method; character; control; control system; developmen

GLOSS

戰(zhàn)役

Nonparametric Curve Estimation from Time Series978-1-4612-3686-3Series ISSN 0930-0325 Series E-ISSN 2197-7186

Clinch

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.