Computational Approaches for Urban Environments

Computational Approaches for Urban Environments
Author: Marco Helbich
Publisher: Springer
Total Pages: 394
Release: 2015-01-22
Genre: Political Science
ISBN: 3319114697

This book aims to promote the synergistic usage of advanced computational methodologies in close relationship to geospatial information across cities of different scales. A rich collection of chapters subsumes current research frontiers originating from disciplines such as geography, urban planning, computer science, statistics, geographic information science and remote sensing. The topics covered in the book are of interest to researchers, postgraduates, practitioners and professionals. The editors hope that the scientific outcome of this book will stimulate future urban-related international and interdisciplinary research, bringing us closer to the vision of a “new science of cities.”

Issues in Housing and Real Estate: 2011 Edition

Issues in Housing and Real Estate: 2011 Edition
Author:
Publisher: ScholarlyEditions
Total Pages: 84
Release: 2012-01-09
Genre: Business & Economics
ISBN: 1464968357

Issues in Housing and Real Estate / 2011 Edition is a ScholarlyBrief™ that delivers timely, authoritative, comprehensive, and specialized information about Housing and Real Estate in a concise format. The editors have built Issues in Housing and Real Estate: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Housing and Real Estate in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Housing and Real Estate: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Flexible Regression and Smoothing

Flexible Regression and Smoothing
Author: Mikis D. Stasinopoulos
Publisher: CRC Press
Total Pages: 641
Release: 2017-04-21
Genre: Mathematics
ISBN: 1351980378

This book is about learning from data using the Generalized Additive Models for Location, Scale and Shape (GAMLSS). GAMLSS extends the Generalized Linear Models (GLMs) and Generalized Additive Models (GAMs) to accommodate large complex datasets, which are increasingly prevalent. In particular, the GAMLSS statistical framework enables flexible regression and smoothing models to be fitted to the data. The GAMLSS model assumes that the response variable has any parametric (continuous, discrete or mixed) distribution which might be heavy- or light-tailed, and positively or negatively skewed. In addition, all the parameters of the distribution (location, scale, shape) can be modelled as linear or smooth functions of explanatory variables. Key Features: Provides a broad overview of flexible regression and smoothing techniques to learn from data whilst also focusing on the practical application of methodology using GAMLSS software in R. Includes a comprehensive collection of real data examples, which reflect the range of problems addressed by GAMLSS models and provide a practical illustration of the process of using flexible GAMLSS models for statistical learning. R code integrated into the text for ease of understanding and replication. Supplemented by a website with code, data and extra materials. This book aims to help readers understand how to learn from data encountered in many fields. It will be useful for practitioners and researchers who wish to understand and use the GAMLSS models to learn from data and also for students who wish to learn GAMLSS through practical examples.

Hedonic Methods in Housing Markets

Hedonic Methods in Housing Markets
Author: Andrea Baranzini
Publisher: Springer Science & Business Media
Total Pages: 283
Release: 2008-09-20
Genre: Business & Economics
ISBN: 0387768157

Cities are growing worldwide and their sprawl is increasingly challenged for its pressure on open spaces and environmental quality. Economic arguments can help to decide about the trade-off between preserving environmental quality and developing housing and business surfaces, provided the benefits of environmental quality are adequately quantified. To this end, this book focuses on the use and advancement of the “hedonic approach”, an economic valuation technique that analyses and quantifies the sources of rent and property price differentials. Starting from theoretical foundations, the hedonic approach is applied to the valuation of natural land use preservation and noise abatement measures, as well as to residential segregation and discrimination, extending the analysis to the role of the buyers and sellers' identity on housing market prices and to the issue of environmental justice.

Regression for Categorical Data

Regression for Categorical Data
Author: Gerhard Tutz
Publisher: Cambridge University Press
Total Pages: 573
Release: 2011-11-21
Genre: Mathematics
ISBN: 1139499580

This book introduces basic and advanced concepts of categorical regression with a focus on the structuring constituents of regression, including regularization techniques to structure predictors. In addition to standard methods such as the logit and probit model and extensions to multivariate settings, the author presents more recent developments in flexible and high-dimensional regression, which allow weakening of assumptions on the structuring of the predictor and yield fits that are closer to the data. A generalized linear model is used as a unifying framework whenever possible in particular parametric models that are treated within this framework. Many topics not normally included in books on categorical data analysis are treated here, such as nonparametric regression; selection of predictors by regularized estimation procedures; ternative models like the hurdle model and zero-inflated regression models for count data; and non-standard tree-based ensemble methods. The book is accompanied by an R package that contains data sets and code for all the examples.

Geographically Weighted Regression

Geographically Weighted Regression
Author: A. Stewart Fotheringham
Publisher: John Wiley & Sons
Total Pages: 282
Release: 2003-02-21
Genre: Science
ISBN: 0470855258

Geographical Weighted Regression (GWR) is a new local modelling technique for analysing spatial analysis. This technique allows local as opposed to global models of relationships to be measured and mapped. This is the first and only book on this technique, offering comprehensive coverage on this new 'hot' topic in spatial analysis. * Provides step-by-step examples of how to use the GWR model using data sets and examples on issues such as house price determinants, educational attainment levels and school performance statistics * Contains a broad discussion of and basic concepts on GWR through to ideas on statistical inference for GWR models * uniquely features accompanying author-written software that allows users to undertake sophisticated and complex forms of GWR within a user-friendly, Windows-based, front-end (see book for details).

Handbook of Regional Science

Handbook of Regional Science
Author: Manfred M. Fischer
Publisher: Springer
Total Pages: 0
Release: 2013-09-17
Genre: Business & Economics
ISBN: 9783642234293

The Handbook of Regional Science is a multi-volume reference work providing a state-of-the-art knowledge on regional science composed by renowned scientists in the field. The Handbook is intended to serve the academic needs of graduate students, and junior and senior scientists in regional science and related fields, with an interest in studying local and regional socio-economic issues. The multi-volume handbook seeks to cover the field of regional science comprehensively, including areas such as regional housing and labor markets, regional economic growth, innovation and regional economic development, new and evolutionary economic geography, location and interaction, the environment and natural resources, spatial analysis and geo-computation as well as spatial statistics and econometrics.

Econometric Models For Industrial Organization

Econometric Models For Industrial Organization
Author: Matthew Shum
Publisher: World Scientific
Total Pages: 154
Release: 2016-12-14
Genre: Business & Economics
ISBN: 981310967X

Economic Models for Industrial Organization focuses on the specification and estimation of econometric models for research in industrial organization. In recent decades, empirical work in industrial organization has moved towards dynamic and equilibrium models, involving econometric methods which have features distinct from those used in other areas of applied economics. These lecture notes, aimed for a first or second-year PhD course, motivate and explain these econometric methods, starting from simple models and building to models with the complexity observed in typical research papers. The covered topics include discrete-choice demand analysis, models of dynamic behavior and dynamic games, multiple equilibria in entry games and partial identification, and auction models.

Multiscale Geographically Weighted Regression

Multiscale Geographically Weighted Regression
Author: A. Stewart Fotheringham
Publisher: CRC Press
Total Pages: 195
Release: 2023-11-15
Genre: Technology & Engineering
ISBN: 1000989704

Multiscale geographically weighted regression (MGWR) is an important method that is used across many disciplines for exploring spatial heterogeneity and modeling local spatial processes. This book introduces the concepts behind local spatial modeling and explains how to model heterogeneous spatial processes within a regression framework. It starts with the basic ideas and fundamentals of local spatial modeling followed by a detailed discussion of scale issues and statistical inference related to MGWR. A comprehensive guide to free, user-friendly, software for MGWR is provided, as well as an example of the application of MGWR to understand voting behavior in the 2020 US Presidential election. Multiscale Geographically Weighted Regression: Theory and Practice is the definitive guide to local regression modeling and the analysis of spatially varying processes, a very cutting-edge, hands-on, and innovative resource. Features Provides a balance between conceptual and technical introduction to local models Explains state-of-the-art spatial analysis technique for multiscale regression modeling Describes best practices and provides a detailed walkthrough of freely available software, through examples and comparisons with other common spatial data modeling techniques Includes a detailed case study to demonstrate methods and software Takes a new and exciting angle on local spatial modeling using MGWR, an innovation to the previous local modeling ‘bible’ GWR The book is ideal for senior undergraduate and graduate students in advanced spatial analysis and GIS courses taught in any spatial science discipline as well as for researchers, academics, and professionals who want to understand how location can affect human behavior through local regression modeling.

Semiparametric Regression for the Applied Econometrician

Semiparametric Regression for the Applied Econometrician
Author: Adonis Yatchew
Publisher: Cambridge University Press
Total Pages: 238
Release: 2003-06-02
Genre: Business & Economics
ISBN: 9780521012263

This book provides an accessible collection of techniques for analyzing nonparametric and semiparametric regression models. Worked examples include estimation of Engel curves and equivalence scales, scale economies, semiparametric Cobb-Douglas, translog and CES cost functions, household gasoline consumption, hedonic housing prices, option prices and state price density estimation. The book should be of interest to a broad range of economists including those working in industrial organization, labor, development, urban, energy and financial economics. A variety of testing procedures are covered including simple goodness of fit tests and residual regression tests. These procedures can be used to test hypotheses such as parametric and semiparametric specifications, significance, monotonicity and additive separability. Other topics include endogeneity of parametric and nonparametric effects, as well as heteroskedasticity and autocorrelation in the residuals. Bootstrap procedures are provided.