Katarzyna Kopczewska – författare
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16 produkter
16 produkter
E-bok
PDF, Engelska, 2025507 kr
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In an era where geo-located point data has become the backbone of socio-economic, environmental, and urban research, understanding spatial density is crucial. Yet the tools for analysing this data have remained scattered and incomplete. Modelling Spatial Density fills a significant gap by providing a comprehensive, practical, and user-friendly guide to modelling spatial density using cutting-edge quantitative methods. Bridging the worlds of spatial statistics, spatial econometrics, and spatial machine learning, Kopczewska introduces a range of established and novel techniques, made accessible through intuitive explanations, open data, and reproducible R code. Lesser and well-known methods are elegantly combined and discussed in non-mathematical language that is accessible to social scientists. The book makes a significant contribution to the synthesis, development, and application of spatial quantitative methods for spatial density in the social and environmental sciences. Writing for researchers, policymakers, and analysts, the author demystifies complex methods, making them accessible to non-mathematicians while maintaining the rigour expected by specialists. With a focus on practical applications, empirical examples, and actionable insights, this resource empowers readers to turn data into evidence for decision-making. Whether you are exploring urban dynamics, environmental challenges, or socio-economic phenomena, this book provides the essential tools for spatial analysis, bringing clarity and precision to your research.
Inbunden, Engelska, 2025
2 283 kr
Skickas inom 3-6 vardagar
In an era where geo-located point data has become the backbone of socio-economic, environmental, and urban research, understanding spatial density is crucial. Yet the tools for analysing this data have remained scattered and incomplete. Modelling Spatial Density fills a significant gap by providing a comprehensive, practical, and user-friendly guide to modelling spatial density using cutting-edge quantitative methods. Bridging the worlds of spatial statistics, spatial econometrics, and spatial machine learning, Kopczewska introduces a range of established and novel techniques, made accessible through intuitive explanations, open data, and reproducible R code. Lesser and well-known methods are elegantly combined and discussed in non-mathematical language that is accessible to social scientists. The book makes a significant contribution to the synthesis, development, and application of spatial quantitative methods for spatial density in the social and environmental sciences. Writing for researchers, policymakers, and analysts, the author demystifies complex methods, making them accessible to non-mathematicians while maintaining the rigour expected by specialists. With a focus on practical applications, empirical examples, and actionable insights, this resource empowers readers to turn data into evidence for decision-making. Whether you are exploring urban dynamics, environmental challenges, or socio-economic phenomena, this book provides the essential tools for spatial analysis, bringing clarity and precision to your research.
Häftad, Engelska, 2025
608 kr
Skickas inom 5-8 vardagar
In an era where geo-located point data has become the backbone of socio-economic, environmental, and urban research, understanding spatial density is crucial. Yet the tools for analysing this data have remained scattered and incomplete. Modelling Spatial Density fills a significant gap by providing a comprehensive, practical, and user-friendly guide to modelling spatial density using cutting-edge quantitative methods. Bridging the worlds of spatial statistics, spatial econometrics, and spatial machine learning, Kopczewska introduces a range of established and novel techniques, made accessible through intuitive explanations, open data, and reproducible R code. Lesser and well-known methods are elegantly combined and discussed in non-mathematical language that is accessible to social scientists. The book makes a significant contribution to the synthesis, development, and application of spatial quantitative methods for spatial density in the social and environmental sciences. Writing for researchers, policymakers, and analysts, the author demystifies complex methods, making them accessible to non-mathematicians while maintaining the rigour expected by specialists. With a focus on practical applications, empirical examples, and actionable insights, this resource empowers readers to turn data into evidence for decision-making. Whether you are exploring urban dynamics, environmental challenges, or socio-economic phenomena, this book provides the essential tools for spatial analysis, bringing clarity and precision to your research.
Häftad, Engelska, 2020
906 kr
Skickas inom 10-15 vardagar
This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different method, explaining how to interpret the results and what conclusions can be drawn. The author team showcases key topics, including unsupervised learning, causal inference, spatial weight matrices, spatial econometrics, heterogeneity and bootstrapping. It is accompanied by a suite of data and R code on Github to help readers practise techniques via replication and exercises. This text will be a valuable resource for advanced students of econometrics, spatial planning and regional science. It will also be suitable for researchers and data scientists working with spatial data.
Inbunden, Engelska, 2020
2 422 kr
Skickas inom 10-15 vardagar
This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different method, explaining how to interpret the results and what conclusions can be drawn. The author team showcases key topics, including unsupervised learning, causal inference, spatial weight matrices, spatial econometrics, heterogeneity and bootstrapping. It is accompanied by a suite of data and R code on Github to help readers practise techniques via replication and exercises. This text will be a valuable resource for advanced students of econometrics, spatial planning and regional science. It will also be suitable for researchers and data scientists working with spatial data.
E-bok
PDF, Engelska, 20201 026 kr
Läs direkt efter köp
This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different method, explaining how to interpret the results and what conclusions can be drawn. The author team showcases key topics, including unsupervised learning, causal inference, spatial weight matrices, spatial econometrics, heterogeneity and bootstrapping. It is accompanied by a suite of data and R code on Github to help readers practise techniques via replication and exercises.
This text will be a valuable resource for advanced students of econometrics, spatial planning and regional science. It will also be suitable for researchers and data scientists working with spatial data.
E-bok
Engelska, 20201 076 kr
Läs direkt efter köp
This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different method, explaining how to interpret the results and what conclusions can be drawn. The author team showcases key topics, including unsupervised learning, causal inference, spatial weight matrices, spatial econometrics, heterogeneity and bootstrapping. It is accompanied by a suite of data and R code on Github to help readers practise techniques via replication and exercises.
This text will be a valuable resource for advanced students of econometrics, spatial planning and regional science. It will also be suitable for researchers and data scientists working with spatial data.
Häftad, Engelska, 2026
971 kr
Kommande
Now in its second edition, Applied Spatial Statistics and Econometrics offers a modern and accessible introduction to spatial data analysis using R. Emphasising reproducibility, real-world datasets, and practical workflows, this comprehensive guide introduces spatial thinking from a critical analytical perspective, highlighting the importance of location, distance, and neighbourhood effects in shaping social and economic phenomena.Readers are guided through foundational concepts, including spatial data structures (areal, point, and grid data), visualisation techniques, and spatial econometric models such as spatial lag, spatial error, and spatial Durbin specifications. Updates reflect the substantial evolution of spatial models and R packages, such as the transition to sf and terra, enhancements to spatstat, new tools for spatial sampling and bootstrap, and fully reproducible analyses with complete R code. Topics include geographically weighted regression, spatial point pattern analysis, DEGURBA classification and spatial principal component analysis.Accompanied by datasets and complete R code on GitHub and RPubs, the book enables readers to replicate analyses and adapt methods to their own research. It is an essential resource for advanced students of econometrics, spatial planning, and regional science, as well as researchers and data scientists seeking to harness the power of spatial analysis for evidence-based insights and policy recommendations.
Inbunden, Engelska, 2026
2 677 kr
Kommande
Now in its second edition, Applied Spatial Statistics and Econometrics offers a modern and accessible introduction to spatial data analysis using R. Emphasising reproducibility, real-world datasets, and practical workflows, this comprehensive guide introduces spatial thinking from a critical analytical perspective, highlighting the importance of location, distance, and neighbourhood effects in shaping social and economic phenomena.Readers are guided through foundational concepts, including spatial data structures (areal, point, and grid data), visualisation techniques, and spatial econometric models such as spatial lag, spatial error, and spatial Durbin specifications. Updates reflect the substantial evolution of spatial models and R packages, such as the transition to sf and terra, enhancements to spatstat, new tools for spatial sampling and bootstrap, and fully reproducible analyses with complete R code. Topics include geographically weighted regression, spatial point pattern analysis, DEGURBA classification and spatial principal component analysis.Accompanied by datasets and complete R code on GitHub and RPubs, the book enables readers to replicate analyses and adapt methods to their own research. It is an essential resource for advanced students of econometrics, spatial planning, and regional science, as well as researchers and data scientists seeking to harness the power of spatial analysis for evidence-based insights and policy recommendations.
Inbunden, Engelska, 2025
3 737 kr
Skickas inom 5-8 vardagar
This pioneering Handbook outlines the ways in which big data and artificial intelligence (AI) are reshaping cities. Leading scholars analyze how innovative computational methods can make use of the vast amounts of data available to gain new insights into urban life, inform policy, and drive innovation.Chapters delve into specific applications of big data and AI including mobility, tourism, and land use, drawing on case studies from diverse urban environments across Europe and North America. Expert authors evaluate future opportunities for leveraging these technologies, addressing the integration of machine learning into spatial econometric models, the use of self-organizing maps to study demographic shifts, and novel approaches to simulating contagion patterns during pandemics. Ultimately, the Handbook emphasizes the potential of AI to contribute to social good.Academics and students in human geography, regional and urban studies, economics, sociology, and management will benefit from this multidisciplinary and comprehensive Handbook. Combining theoretical insights with practical applications, it is also a valuable resource for policymakers and practitioners interested in the ongoing digital transformation of urban spaces.
E-bok
PDF, Engelska, 2025880 kr
Läs direkt efter köp
This pioneering Handbook outlines the ways in which big data and artificial intelligence (AI) are reshaping cities. Leading scholars analyze how innovative computational methods can make use of the vast amounts of data available to gain new insights into urban life, inform policy, and drive innovation.
Chapters delve into specific applications of big data and AI including mobility, tourism, and land use, drawing on case studies from diverse urban environments across Europe and North America. Expert authors evaluate future opportunities for leveraging these technologies, addressing the integration of machine learning into spatial econometric models, the use of self-organizing maps to study demographic shifts, and novel approaches to simulating contagion patterns during pandemics. Ultimately, the Handbook emphasizes the potential of AI to contribute to social good.
Academics and students in human geography, regional and urban studies, economics, sociology, and management will benefit from this multidisciplinary and comprehensive Handbook. Combining theoretical insights with practical applications, it is also a valuable resource for policymakers and practitioners interested in the ongoing digital transformation of urban spaces.
Inbunden, Engelska, 2017
1 333 kr
Skickas inom 10-15 vardagar
This book explores statistical models in regional specialization, presenting a brand new measure. It begins by reviewing existing indicators and models of regional specialization before outlining a newly created, spatially embedded model of specialization based on the spatial distribution of firms. It addresses the various applications of the model, and how the model can be used in regional policy.
E-bok
Engelska, 20171 785 kr
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This book explores statistical models in regional specialization, presenting a brand new measure. It begins by reviewing existing indicators and models of regional specialization before outlining a newly created, spatially embedded model of specialization based on the spatial distribution of firms. It addresses the various applications of the model, and how the model can be used in regional policy.
Häftad, Engelska, 2018
1 333 kr
Skickas inom 10-15 vardagar
This book explores statistical models in regional specialization, presenting a brand new measure. It begins by reviewing existing indicators and models of regional specialization before outlining a newly created, spatially embedded model of specialization based on the spatial distribution of firms. It addresses the various applications of the model, and how the model can be used in regional policy.
E-bok
PDF, Engelska, 2006221 kr
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Research Paper (postgraduate) from the year 2003 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: advanced, Warsaw University (Faculty of Economic Sciences), language: English, abstract: European integration will have a real influence on the shape of the financial market in Poland and in other former socialistic countries which undergone the transformation. To stop the tendency of weakening of Polish stock exchange it is important to recognize mechanisms influencing the decisions of companies about the public sale of shares. Decision of companies about the entry on the stock exchange is driven with the expectation that it will help them in the realization of the particular goals. There are many primary reasons for issuing shares, among other to gain the capital on investments, to acquire prestige, to increase sale etc. In Poland till now the entry on the stock exchange of some companies was a method of the privatization, however this process extinguishes. Going public companies will be owned by private businessmen. Hence, very important is to recognize the original mechanisms of initial public offering (IPO). The analysis of IPO effects, enforced with the use of panel models points, that thanks to funds from going public the company realize investment projects and use resources in compliance with declared destination, i.e. on investments, and not on the debts repayment. Public companies do not change their previous capital structure, the debts after the entry on the stock exchange grow to the level from before IPO. Listing on the stock exchange raises the size of the company, but lowers the rate of its growth and decreases the profitability. Findings from research confirm hypotheses that companies go public from the opportunistic motives and then by the way they realize investment programmes.
E-bok
PDF, Engelska, 2006221 kr
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Research Paper (postgraduate) from the year 2005 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: advanced, Warsaw University (Faculty of Economic Sciences), language: English, abstract: The purpose shares split is to divide nominal value in given proportion eg. 2:1, 5:4 etc, what hat involves the proportional reduction of the price Splits are conducted on shares, both traded public and in private turnover. From the rational point of view split should have no other consequences for investors and for share price and should be treated as a cosmetic correction. For shareholders, split changes a nominal amount of shares, but it does not change the value of portfolio. Shareholders rights, Cash Flow and equity of company stay unchanged. In the history of the world stock exchanges the first shares splits took place in 1927. The earliest research is dated 1933 (Doodley 1933), but the top of popularity splits reached recently, since the 90. Easley, O Hara, Saar (2001) report that the most of splits took place in 1997 on NYSE, when about 235 companies made a split. On average about 10% of firms decide each year to lower the share price. Some of companies made a split for many times as e.g. Johnson & Johnson (6 splits since 1970), Bouygues (12 splits since 1979) etc. The main question of researchers, investors and companies is why to make a split? . Still the explicit motive of split is unknown. There are many hypothesis and case studies in the literature. All appearing hypothesis are clustered around some periods of time. In history of splits there are three main groups to be distinguished: Since 30 up to 70 - from splits appearance to the market transformation during fuel crisis Since 70 up to 1998 - form the development of modern financial instruments to the crisis of new technology companies Since 1998 up to now and more Given above classification concerns mainly U.S. market, the most developed one in the world. But one should remember, that this market serves as a indicator of investments mood. It gives a direction of development and influences trends all over the world. So, everything what happens on the U.S. market is also about the rest of the world, but with some time lag.