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Spatial Econometrics Using Microdata
Spatial Econometrics Using Microdata
Knygos.lt klubas Knygos.lt nariams
240,37 €
-30%
Įprastai
343,39 €
  • Išsiųsime per 12–18 d.d.
This book provides an introduction to spatial analyses concerning disaggregated (or micro) spatial data. Particular emphasis is put on spatial data compilation and the structuring of the connections between the observations. Descriptive analysis methods of spatial data are presented in order to identify and measure the spatial, global and local dependency. The authors then focus on autoregressive spatial models, to control the problem of spatial dependency between the residues of a basic linear…
  • Leidėjas:
  • Metai: 2014
  • Puslapiai: 242
  • ISBN-10: 1848214685
  • ISBN-13: 9781848214682
  • Formatas: 16 x 23.6 x 2 cm, kieti viršeliai
  • Kalba: Anglų

Spatial Econometrics Using Microdata (el. knyga) (skaityta knyga) | knygos.lt

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This book provides an introduction to spatial analyses concerning disaggregated (or micro) spatial data.

Particular emphasis is put on spatial data compilation and the structuring of the connections between the observations. Descriptive analysis methods of spatial data are presented in order to identify and measure the spatial, global and local dependency.

The authors then focus on autoregressive spatial models, to control the problem of spatial dependency between the residues of a basic linear statistical model, thereby contravening one of the basic hypotheses of the ordinary least squares approach.

This book is a popularized reference for students looking to work with spatialized data, but who do not have the advanced statistical theoretical basics.

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Daugiau
  • Autorius: Diègo Legros
  • Leidėjas:
  • Metai: 2014
  • Puslapiai: 242
  • ISBN-10: 1848214685
  • ISBN-13: 9781848214682
  • Formatas: 16 x 23.6 x 2 cm, kieti viršeliai
  • Kalba: Anglų

This book provides an introduction to spatial analyses concerning disaggregated (or micro) spatial data.

Particular emphasis is put on spatial data compilation and the structuring of the connections between the observations. Descriptive analysis methods of spatial data are presented in order to identify and measure the spatial, global and local dependency.

The authors then focus on autoregressive spatial models, to control the problem of spatial dependency between the residues of a basic linear statistical model, thereby contravening one of the basic hypotheses of the ordinary least squares approach.

This book is a popularized reference for students looking to work with spatialized data, but who do not have the advanced statistical theoretical basics.

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