Isbn: 9781316610855 - inferential network analysis (33 risultati)

Paperback. Condizione: Fair. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

paperback. Condizione: Very Good.

paperback. Condizione: Good. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Condizione: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.…

Paperback. Condizione: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

Paperback. Condizione: new. Paperback. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses. Introduces foundational statistical models for network data, augmenting theoretical discussion with applications across the social sciences implemented in the R language. An introductory text or reference for researchers, graduate students, and advanced undergraduate students across the social, mathematical, computational and physical sciences. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condizione: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.…

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: New. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses.…

Condizione: new.

Paperback. Condizione: New. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses.…

Condizione: New. pp. 250.

Condizione: New.

Paperback. Condizione: New.

Condizione: New. In.

Condizione: New. 2020. Paperback. . . . . .

Paperback. Condizione: Brand New. 291 pages. 8.75x6.00x0.75 inches. In Stock.

Condizione: As New. Unread book in perfect condition.

Condizione: New. pp. 250.

Paperback / softback. Condizione: New. New copy - Usually dispatched within 3 working days.

Condizione: New. 2020. Paperback. . . . . . Books ship from the US and Ireland.

Condizione: New. pp. 250.

Condizione: NEW.

Paperback. Condizione: Brand New. 291 pages. 8.75x6.00x0.75 inches. In Stock.

Condizione: New. Introduces foundational statistical models for network data, augmenting theoretical discussion with applications across the social sciences implemented in the R language. An introductory text or reference for researchers, graduate students, and advanced und.

Paperback. Condizione: New. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses.…

Taschenbuch. Condizione: Neu. Neuware - This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses.…

Paperback. Condizione: new. Paperback. This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses. Introduces foundational statistical models for network data, augmenting theoretical discussion with applications across the social sciences implemented in the R language. An introductory text or reference for researchers, graduate students, and advanced undergraduate students across the social, mathematical, computational and physical sciences. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…