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Titlebook: Numerical Ecology with R; Daniel Borcard,François Gillet,Pierre Legendre Book 2018Latest edition Springer International Publishing AG, par

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Spatial Analysis of Ecological Data, variables describing spatial structures derived from the coordinates of the sites or from the neighbourhood relationships among sites. These variables are used to model the spatial structures of ecological data by means of multiple regression or canonical ordination, and to identify significant spa
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Daniel Borcard,François Gillet,Pierre Legendresists of contributions given in honor of Wolfgang J.R. Hoefer. Space and time discretizing time domain methods for electromagnetic full-wave simulation have emerged as key numerical methods in computational electromagnetics. Time domain methods are versatile and can be applied to the solution of a w
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Daniel Borcard,François Gillet,Pierre Legendreion/neural network technique (SSE-NN), and a recurrent neural network (RNN) technique are described. In the SSE-NN approach, the model is a hierarchical structure with two levels. In the lower level, a neural network maps the geometrical/physical parameters of the passive component into coefficient
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Daniel Borcard,François Gillet,Pierre LegendreOffers an up-to-date, practical guide to numerical ecology from leaders in the field.Provides complete data sets, functions and scripts.Includes examples with extensive commentaries
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Introduction,This chapter explains the importance of numerical ecology as well as the interest of using R in this field. It exposes the structure of the book and presents the main data sets used in the applications. Links to the datasets and R scripts are provided. This chapter also explains how to use the book for maximum efficiency.
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