Robust Small Area Estimation Under Spatial Non Stationarity For Unit Level Models
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Robust Small Area Estimation Under Spatial Non Stationarity For Unit Level Models
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Author : Claudia Baldermann
language : en
Publisher:
Release Date : 2017
Robust Small Area Estimation Under Spatial Non Stationarity For Unit Level Models written by Claudia Baldermann and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Analysis Of Poverty Data By Small Area Estimation
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Author : Monica Pratesi
language : en
Publisher: John Wiley & Sons
Release Date : 2016-02-23
Analysis Of Poverty Data By Small Area Estimation written by Monica Pratesi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-23 with Mathematics categories.
A comprehensive guide to implementing SAE methods for poverty studies and poverty mapping There is an increasingly urgent demand for poverty and living conditions data, in relation to local areas and/or subpopulations. Policy makers and stakeholders need indicators and maps of poverty and living conditions in order to formulate and implement policies, (re)distribute resources, and measure the effect of local policy actions. Small Area Estimation (SAE) plays a crucial role in producing statistically sound estimates for poverty mapping. This book offers a comprehensive source of information regarding the use of SAE methods adapted to these distinctive features of poverty data derived from surveys and administrative archives. The book covers the definition of poverty indicators, data collection and integration methods, the impact of sampling design, weighting and variance estimation, the issue of SAE modelling and robustness, the spatio-temporal modelling of poverty, and the SAE of the distribution function of income and inequalities. Examples of data analyses and applications are provided, and the book is supported by a website describing scripts written in SAS or R software, which accompany the majority of the presented methods. Key features: Presents a comprehensive review of SAE methods for poverty mapping Demonstrates the applications of SAE methods using real-life case studies Offers guidance on the use of routines and choice of websites from which to download them Analysis of Poverty Data by Small Area Estimation offers an introduction to advanced techniques from both a practical and a methodological perspective, and will prove an invaluable resource for researchers actively engaged in organizing, managing and conducting studies on poverty.
Applied Statistical Methods
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Author : David D. Hanagal
language : en
Publisher: Springer Nature
Release Date : 2022-04-13
Applied Statistical Methods written by David D. Hanagal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-13 with Mathematics categories.
This book collects select contributions presented at the International Conference on Importance of Statistics in Global Emerging (ISGES 2020) held at the Department of Mathematics and Statistics, University of Pune, Maharashtra, India, from 2–4 January 2020. It discusses recent developments in several areas of statistics with applications of a wide range of key topics, including small area estimation techniques, Bayesian models for small areas, ranked set sampling, fuzzy supply chain, probabilistic supply chain models, dynamic Gaussian process models, grey relational analysis and multi-item inventory models, and more. The possible use of other models, including generalized Lindley shared frailty models, Benktander Gibrat risk model, decision-consistent randomization method for SMART designs and different reliability models are also discussed. This book includes detailed worked examples and case studies that illustrate the applications of recently developed statistical methods, making it a valuable resource for applied statisticians, students, research project leaders and practitioners from various marginal disciplines and interdisciplinary research.
A Course On Small Area Estimation And Mixed Models
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Author : Domingo Morales
language : en
Publisher: Springer Nature
Release Date : 2021-03-12
A Course On Small Area Estimation And Mixed Models written by Domingo Morales and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-12 with Social Science categories.
This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation. It presents the theory in a rigorous way and compares and contrasts various statistical methodologies, helping readers understand how to develop new methodologies for small area estimation. It also includes numerous sample applications of small area estimation techniques. The underlying R code is provided in the text and applied to four datasets that mimic data from labor markets and living conditions surveys, where the socioeconomic indicators include the small area estimation of total unemployment, unemployment rates, average annual household incomes and poverty indicators. Given its scope, the book will be useful for master and PhD students, and for official and other applied statisticians.
The Econometric Analysis Of Non Stationary Spatial Panel Data
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Author : Michael Beenstock
language : en
Publisher: Springer
Release Date : 2019-03-27
The Econometric Analysis Of Non Stationary Spatial Panel Data written by Michael Beenstock and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-27 with Business & Economics categories.
This monograph deals with spatially dependent nonstationary time series in a way accessible to both time series econometricians wanting to understand spatial econometics, and spatial econometricians lacking a grounding in time series analysis. After charting key concepts in both time series and spatial econometrics, the book discusses how the spatial connectivity matrix can be estimated using spatial panel data instead of assuming it to be exogenously fixed. This is followed by a discussion of spatial nonstationarity in spatial cross-section data, and a full exposition of non-stationarity in both single and multi-equation contexts, including the estimation and simulation of spatial vector autoregression (VAR) models and spatial error correction (ECM) models. The book reviews the literature on panel unit root tests and panel cointegration tests for spatially independent data, and for data that are strongly spatially dependent. It provides for the first time critical valuesfor panel unit root tests and panel cointegration tests when the spatial panel data are weakly or spatially dependent. The volume concludes with a discussion of incorporating strong and weak spatial dependence in non-stationary panel data models. All discussions are accompanied by empirical testing based on a spatial panel data of house prices in Israel.
Robust Small Area Estimation Under Spatial Non Stationarity
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Author :
language : en
Publisher:
Release Date : 2016
Robust Small Area Estimation Under Spatial Non Stationarity written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Geographically weighted small area methods have been studied in literature for small area estimation. Although these approaches are useful for the estimation of small area means efficiently under strict parametric assumptions, they can be very sensitive to outliers in the data. In this paper, we propose a robust extension of the geographically weighted empirical best linear unbiased predictor (GWEBLUP). In particular, we introduce robust projective and predictive small area estimators under spatial non-stationarity. Mean squared error estimation is performed by two different analytic approaches that account for the spatial structure in the data. The results from the model-based simulations indicate that the proposed approach may lead to gains in terms of efficiency. Finally, the methodology is demonstrated in an illustrative application for estimating the average total cash costs for farms in Australia.
Geographically Weighted Regression
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Author : A. Stewart Fotheringham
language : en
Publisher: John Wiley & Sons
Release Date : 2003-02-21
Geographically Weighted Regression written by A. Stewart Fotheringham and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-02-21 with Science categories.
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).
Essays In Honor Of M Hashem Pesaran
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Author : Alexander Chudik
language : en
Publisher: Emerald Group Publishing
Release Date : 2022-01-18
Essays In Honor Of M Hashem Pesaran written by Alexander Chudik and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-18 with Business & Economics categories.
The collection of chapters in Volume 43 Part B of Advances in Econometrics serves as a tribute to one of the most innovative, influential, and productive econometricians of his generation, Professor M. Hashem Pesaran.
Land Change Science
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Author : Garik Gutman
language : en
Publisher: Springer Science & Business Media
Release Date : 2004-10-29
Land Change Science written by Garik Gutman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-10-29 with Science categories.
This volume is a synthesis of the NASA funded work under the Land-Cover and Land-Use Change Program. Hundreds of scientists have worked for the past eight years to understand one of the most important forces that is changing our planet-human impacts on land cover, that is land use. Its contributions span the natural and the social sciences, and apply state-of-the-art techniques for understanding the earth: satellite remote sensing, geographic information systems, modeling, and advanced computing. It brings together detailed case studies, regional analyses, and globally scaled mapping efforts. This is the most organized effort made to understand the dominant force that has been responsible for changing the Earth’s biosphere. Audience: This publication will be of interest to students, scientists, and policy makers. This volume includes a CD-ROM containing full color images of a selection of illustrations which are printed in black-and-white in the book.
Spatial Econometric Interaction Modelling
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Author : Roberto Patuelli
language : en
Publisher: Springer
Release Date : 2016-07-25
Spatial Econometric Interaction Modelling written by Roberto Patuelli and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-25 with Business & Economics categories.
This contributed volume applies spatial and space-time econometric methods to spatial interaction modeling. The first part of the book addresses general cutting-edge methodological questions in spatial econometric interaction modeling, which concern aspects such as coefficient interpretation, constrained estimation, and scale effects. The second part deals with technical solutions to particular estimation issues, such as intraregional flows, Bayesian PPML and VAR estimation. The final part presents a number of empirical applications, ranging from interregional tourism competition and domestic trade to space-time migration modeling and residential relocation.