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Título : Chemometrics with R : Multivariate Data Analysis in the Natural Sciences and Life Sciences Tipo de documento: documento electrónico Autores: Wehrens, Ron ; SpringerLink (Online service) Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2011 Colección: Use R Número de páginas: XIV, 286 p. 99 illus Il.: online resource ISBN/ISSN/DL: 978-3-642-17841-2 Idioma : Inglés (eng) Palabras clave: Life sciences Chemoinformatics Bioinformatics Computational biology Statistics Sciences Computer Applications in Chemistry for Sciences, Medicine, Health Appl. Clasificación: 51 Matemáticas Resumen: "Chemometrics with R" offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a complete description of the general data analysis paradigm, from exploratory analysis to modeling to validation. Several more specific topics from the area of chemometrics are included in a special section. The corresponding R code is provided for all the examples in the book; scripts, functions and data are available in a separate, publicly available R package. For researchers working in the life sciences, the book can also serve as an easy-to-use primer on R Nota de contenido: Introduction -- Part I Preliminaries: Data -- Preprocessing -- Part II Exploratory Analysis: Principal Component Analysis -- Self-Organizing Maps -- Clustering -- Part III Modelling: Classification -- Multivariate Regression -- Part IV Model Inspection: Validation -- Variable Selection -- Part V Applications: Chemometric -- Part VI Appendices: R packages Used in This Book -- References -- Index En línea: http://dx.doi.org/10.1007/978-3-642-17841-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33405 Chemometrics with R : Multivariate Data Analysis in the Natural Sciences and Life Sciences [documento electrónico] / Wehrens, Ron ; SpringerLink (Online service) . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2011 . - XIV, 286 p. 99 illus : online resource. - (Use R) .
ISBN : 978-3-642-17841-2
Idioma : Inglés (eng)
Palabras clave: Life sciences Chemoinformatics Bioinformatics Computational biology Statistics Sciences Computer Applications in Chemistry for Sciences, Medicine, Health Appl. Clasificación: 51 Matemáticas Resumen: "Chemometrics with R" offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a complete description of the general data analysis paradigm, from exploratory analysis to modeling to validation. Several more specific topics from the area of chemometrics are included in a special section. The corresponding R code is provided for all the examples in the book; scripts, functions and data are available in a separate, publicly available R package. For researchers working in the life sciences, the book can also serve as an easy-to-use primer on R Nota de contenido: Introduction -- Part I Preliminaries: Data -- Preprocessing -- Part II Exploratory Analysis: Principal Component Analysis -- Self-Organizing Maps -- Clustering -- Part III Modelling: Classification -- Multivariate Regression -- Part IV Model Inspection: Validation -- Variable Selection -- Part V Applications: Chemometric -- Part VI Appendices: R packages Used in This Book -- References -- Index En línea: http://dx.doi.org/10.1007/978-3-642-17841-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33405 Ejemplares
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Título : Model Based Inference in the Life Sciences: A Primer on Evidence Tipo de documento: documento electrónico Autores: David R. Anderson ; SpringerLink (Online service) Editorial: New York, NY : Springer New York Fecha de publicación: 2008 Número de páginas: XXIV, 184 p. 8 illus Il.: online resource ISBN/ISSN/DL: 978-0-387-74075-1 Idioma : Inglés (eng) Palabras clave: Life sciences Epidemiology Ecology Evolutionary biology Statistics Social Sciences for Sciences, Medicine, Health Environmental Monitoring/Analysis Biology Methodology of the Clasificación: 51 Matemáticas Resumen: The abstract concept of "information" can be quantified and this has led to many important advances in the analysis of data in the empirical sciences. This text focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The fundamental science question relates to the empirical evidence for hypotheses in this set—a formal strength of evidence. Kullback-Leibler information is the information lost when a model is used to approximate full reality. Hirotugu Akaike found a link between K-L information (a cornerstone of information theory) and the maximized log-likelihood (a cornerstone of mathematical statistics). This combination has become the basis for a new paradigm in model based inference. The text advocates formal inference from all the hypotheses/models in the a priori set—multimodel inference. This compelling approach allows a simple ranking of the science hypothesis and their models. Simple methods are introduced for computing the likelihood of model i, given the data; the probability of model i, given the data; and evidence ratios. These quantities represent a formal strength of evidence and are easy to compute and understand, given the estimated model parameters and associated quantities (e.g., residual sum of squares, maximized log-likelihood, and covariance matrices). Additional forms of multimodel inference include model averaging, unconditional variances, and ways to rank the relative importance of predictor variables. This textbook is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals in various universities, agencies or institutes. Readers are expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameter estimation. DAVID R. ANDERSON retired recently from serving as a senior scientist with the U.S. Geological Survey and professor in the Department of Fish, Wildlife, and Conservation Biology at Colorado State University. He has an emeritus professorship at CSU and is president of the Applied Information Company in Fort Collins. He has authored 18 scientific books and research monographs and over 100 journal publications. He has received a variety of awards, including U.S. Department of Interior’s Meritorious Service Award and The Wildlife Society’s 2004 Aldo Leopold Memorial Award and Medal Nota de contenido: Introduction: Science Hypotheses and Science Philosophy -- Data and Models -- Information Theory and Entropy -- Quantifying the Evidence About Science Hypotheses -- Multimodel Inference -- Advanced Topics -- Summary En línea: http://dx.doi.org/10.1007/978-0-387-74075-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34188 Model Based Inference in the Life Sciences: A Primer on Evidence [documento electrónico] / David R. Anderson ; SpringerLink (Online service) . - New York, NY : Springer New York, 2008 . - XXIV, 184 p. 8 illus : online resource.
ISBN : 978-0-387-74075-1
Idioma : Inglés (eng)
Palabras clave: Life sciences Epidemiology Ecology Evolutionary biology Statistics Social Sciences for Sciences, Medicine, Health Environmental Monitoring/Analysis Biology Methodology of the Clasificación: 51 Matemáticas Resumen: The abstract concept of "information" can be quantified and this has led to many important advances in the analysis of data in the empirical sciences. This text focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The fundamental science question relates to the empirical evidence for hypotheses in this set—a formal strength of evidence. Kullback-Leibler information is the information lost when a model is used to approximate full reality. Hirotugu Akaike found a link between K-L information (a cornerstone of information theory) and the maximized log-likelihood (a cornerstone of mathematical statistics). This combination has become the basis for a new paradigm in model based inference. The text advocates formal inference from all the hypotheses/models in the a priori set—multimodel inference. This compelling approach allows a simple ranking of the science hypothesis and their models. Simple methods are introduced for computing the likelihood of model i, given the data; the probability of model i, given the data; and evidence ratios. These quantities represent a formal strength of evidence and are easy to compute and understand, given the estimated model parameters and associated quantities (e.g., residual sum of squares, maximized log-likelihood, and covariance matrices). Additional forms of multimodel inference include model averaging, unconditional variances, and ways to rank the relative importance of predictor variables. This textbook is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals in various universities, agencies or institutes. Readers are expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameter estimation. DAVID R. ANDERSON retired recently from serving as a senior scientist with the U.S. Geological Survey and professor in the Department of Fish, Wildlife, and Conservation Biology at Colorado State University. He has an emeritus professorship at CSU and is president of the Applied Information Company in Fort Collins. He has authored 18 scientific books and research monographs and over 100 journal publications. He has received a variety of awards, including U.S. Department of Interior’s Meritorious Service Award and The Wildlife Society’s 2004 Aldo Leopold Memorial Award and Medal Nota de contenido: Introduction: Science Hypotheses and Science Philosophy -- Data and Models -- Information Theory and Entropy -- Quantifying the Evidence About Science Hypotheses -- Multimodel Inference -- Advanced Topics -- Summary En línea: http://dx.doi.org/10.1007/978-0-387-74075-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34188 Ejemplares
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Título : Complex Systems and Society : Modeling and Simulation Tipo de documento: documento electrónico Autores: Nicola Bellomo ; SpringerLink (Online service) ; Giulia Ajmone Marsan ; Tosin, Andrea Editorial: New York, NY : Springer New York Fecha de publicación: 2013 Otro editor: Imprint: Springer Colección: SpringerBriefs in Mathematics, ISSN 2191-8198 Número de páginas: XII, 90 p. 12 illus. in color Il.: online resource ISBN/ISSN/DL: 978-1-4614-7242-1 Idioma : Inglés (eng) Palabras clave: Mathematics Applied mathematics Engineering Game theory System Mathematical models Economic Social sciences Modeling and Industrial Theory/Quantitative Economics/Mathematical Methods Complex Systems Sciences, general Theory, Economics, Behav. Sciences Applications of Clasificación: 51 Matemáticas Resumen: This work aims to foster the interdisciplinary dialogue between mathematicians and socio-economic scientists. Interaction among scholars and practitioners traditionally coming from different research areas is necessary more than ever in order to better understand many real-world problems we face today. On the one hand, mathematicians need economists and social scientists to better address the methodologies they design in a more realistic way; on the other hand, economists and social scientists need to be aware of sound mathematical modelling tools in order to understand and, ultimately, solve the complex problems they encounter in their research. With this goal in mind, this work is designed to take into account a multidisciplinary approach that will encourage the transfer of knowledge, ideas, and methodology from one discipline to the other. In particular, the work has three main themes: Demystifying and unravelling complex systems; Introducing models of individual behaviours in the social and economic sciences; Modelling socio-economic sciences as complex living systems. Specific tools examined in the work include a recently developed modelling approach using stochastic game theory within the framework of statistical mechanics and progressing up to modeling Darwinian evolution. Special attention is also devoted to social network theory as a fundamental instrument for the understanding of socio-economic systems Nota de contenido: 1. The Role of Individual Behaviors in Socio-Economic Sciences -- 2. Mathematical Tools for Modeling Social Complex Systems -- 3. Modeling Cooperation and Competition in Socio-Economic Systems -- 4. Welfare Policy: Applications and Simulations -- 5. Forward Look at Research Perspectives -- References En línea: http://dx.doi.org/10.1007/978-1-4614-7242-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32342 Complex Systems and Society : Modeling and Simulation [documento electrónico] / Nicola Bellomo ; SpringerLink (Online service) ; Giulia Ajmone Marsan ; Tosin, Andrea . - New York, NY : Springer New York : Imprint: Springer, 2013 . - XII, 90 p. 12 illus. in color : online resource. - (SpringerBriefs in Mathematics, ISSN 2191-8198) .
ISBN : 978-1-4614-7242-1
Idioma : Inglés (eng)
Palabras clave: Mathematics Applied mathematics Engineering Game theory System Mathematical models Economic Social sciences Modeling and Industrial Theory/Quantitative Economics/Mathematical Methods Complex Systems Sciences, general Theory, Economics, Behav. Sciences Applications of Clasificación: 51 Matemáticas Resumen: This work aims to foster the interdisciplinary dialogue between mathematicians and socio-economic scientists. Interaction among scholars and practitioners traditionally coming from different research areas is necessary more than ever in order to better understand many real-world problems we face today. On the one hand, mathematicians need economists and social scientists to better address the methodologies they design in a more realistic way; on the other hand, economists and social scientists need to be aware of sound mathematical modelling tools in order to understand and, ultimately, solve the complex problems they encounter in their research. With this goal in mind, this work is designed to take into account a multidisciplinary approach that will encourage the transfer of knowledge, ideas, and methodology from one discipline to the other. In particular, the work has three main themes: Demystifying and unravelling complex systems; Introducing models of individual behaviours in the social and economic sciences; Modelling socio-economic sciences as complex living systems. Specific tools examined in the work include a recently developed modelling approach using stochastic game theory within the framework of statistical mechanics and progressing up to modeling Darwinian evolution. Special attention is also devoted to social network theory as a fundamental instrument for the understanding of socio-economic systems Nota de contenido: 1. The Role of Individual Behaviors in Socio-Economic Sciences -- 2. Mathematical Tools for Modeling Social Complex Systems -- 3. Modeling Cooperation and Competition in Socio-Economic Systems -- 4. Welfare Policy: Applications and Simulations -- 5. Forward Look at Research Perspectives -- References En línea: http://dx.doi.org/10.1007/978-1-4614-7242-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32342 Ejemplares
Signatura Medio Ubicación Sección Estado ningún ejemplar Advances in Statistical Methods for the Health Sciences / SpringerLink (Online service) ; Jean-Louis Auget ; Nagraj Balakrishnan ; Mesbah, Mounir ; Molenberghs, Geert (2007)
Título : Advances in Statistical Methods for the Health Sciences : Applications to Cancer and AIDS Studies, Genome Sequence Analysis, and Survival Analysis Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Jean-Louis Auget ; Nagraj Balakrishnan ; Mesbah, Mounir ; Molenberghs, Geert Editorial: Boston, MA : Birkhäuser Boston Fecha de publicación: 2007 Colección: Statistics for Industry and Technology, ISSN 2364-6241 Número de páginas: XLII, 540 p Il.: online resource ISBN/ISSN/DL: 978-0-8176-4542-7 Idioma : Inglés (eng) Palabras clave: Mathematics Applied mathematics Engineering Probabilities Statistics Probability Theory and Stochastic Processes Applications of for Life Sciences, Medicine, Health Sciences Statistical Methods Clasificación: 51 Matemáticas Resumen: Statistical methods have become increasingly important and now form integral part of research in the health sciences. Many sophisticated methodologies have been developed for specific applications and problems. This self-contained volume, an outgrowth of an "International Conference on Statistical Methods in Health Sciences," covers a wide range of topics pertaining to new statistical methods and novel applications in the health sciences. The chapters, written by leading experts in their respective fields, are thematically divided into the following areas: * Prognostic studies and general epidemiology * Pharmacovigilance * Quality of life * Survival analysis * Clustering * Safety and efficacy assessment * Clinical design * Models for the environment * Genomic analysis * Animal health This comprehensive volume will be highly useful an of great interest to the health science community as well as practitioners, researchers, and graduate students in applied probability, statistics, and biostatistics. Nota de contenido: Prognostic Studies and General Epidemiology -- Systematic Review of Multiple Studies of Prognosis: The Feasibility of Obtaining Individual Patient Data -- On Statistical Approaches for the Multivariable Analysis of Prognostic Marker Studies -- Where Next for Evidence Synthesis of Prognostic Marker Studies? Improving the Quality and Reporting of Primary Studies to Facilitate Clinically Relevant Evidence-Based Results -- Pharmacovigilance -- Sentinel Event Methods for Monitoring Unanticipated Adverse Events -- Spontaneous Reporting System Modelling for the Evaluation of Automatic Signal Generation Methods in Pharmacovigilance -- Quality of Life -- Latent Covariates in Generalized Linear Models: A Rasch Model Approach -- Sequential Analysis of Quality of Life Measurements with the Mixed Partial Credit Model -- A Parametric Degradation Model Used in Reliability, Survival Analysis, and Quality of Life -- Agreement Between Two Ratings with Different Ordinal Scales -- Survival Analysis -- The Role of Correlated Frailty Models in Studies of Human Health, Ageing, and Longevity -- Prognostic Factors and Prediction of Residual Survival for Hospitalized Elderly Patients -- New Models and Methods for Survival Analysis of Experimental Data -- Uniform Consistency for Conditional Lifetime Distribution Estimators Under Random Right-Censorship -- Sequential Estimation for the Semiparametric Additive Hazard Model -- Variance Estimation of a Survival Function with Doubly Censored Failure Time Data -- Clustering -- Statistical Models and Artificial Neural Networks: Supervised Classification and Prediction Via Soft Trees -- Multilevel Clustering for Large Databases -- Neural Networks: An Application for Predicting Smear Negative Pulmonary Tuberculosis -- Assessing Drug Resistance in HIV Infection Using Viral Load Using Segmented Regression -- Assessment of Treatment Effects on HIV Pathogenesis Under Treatment By State Space Models -- Safety and Efficacy Assessment -- Safety Assessment Versus Efficacy Assessment -- Cancer Clinical Trials with Efficacy and Toxicity Endpoints: A Simulation Study to Compare Two Nonparametric Methods -- Safety Assessment in Pilot Studies When Zero Events Are Observed -- Clinical Designs -- An Assessment of Up-and-Down Designs and Associated Estimators in Phase I Trials -- Design of Multicentre Clinical Trials with Random Enrolment -- Statistical Methods for Combining Clinical Trial Phases II And III -- SCPRT: A Sequential Procedure That Gives Another Reason to Stop Clinical Trials Early -- Models for the Environment -- Seasonality Assessment for Biosurveillance Systems -- Comparison of Three Convolution Prior Spatial Models for Cancer Incidence -- Longitudinal Analysis of Short-Term Bronchiolitis Air Pollution Association Using Semiparametric Models -- Genomic Analysis -- Are There Correlated Genomic Substitutions? -- Animal Health -- Swiss Federal Veterinary Office Risk Assessments: Advantages and Limitations of The Qualitative Method -- Qualitative Risk Analysis in Animal Health: A Methodological Example En línea: http://dx.doi.org/10.1007/978-0-8176-4542-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34547 Advances in Statistical Methods for the Health Sciences : Applications to Cancer and AIDS Studies, Genome Sequence Analysis, and Survival Analysis [documento electrónico] / SpringerLink (Online service) ; Jean-Louis Auget ; Nagraj Balakrishnan ; Mesbah, Mounir ; Molenberghs, Geert . - Boston, MA : Birkhäuser Boston, 2007 . - XLII, 540 p : online resource. - (Statistics for Industry and Technology, ISSN 2364-6241) .
ISBN : 978-0-8176-4542-7
Idioma : Inglés (eng)
Palabras clave: Mathematics Applied mathematics Engineering Probabilities Statistics Probability Theory and Stochastic Processes Applications of for Life Sciences, Medicine, Health Sciences Statistical Methods Clasificación: 51 Matemáticas Resumen: Statistical methods have become increasingly important and now form integral part of research in the health sciences. Many sophisticated methodologies have been developed for specific applications and problems. This self-contained volume, an outgrowth of an "International Conference on Statistical Methods in Health Sciences," covers a wide range of topics pertaining to new statistical methods and novel applications in the health sciences. The chapters, written by leading experts in their respective fields, are thematically divided into the following areas: * Prognostic studies and general epidemiology * Pharmacovigilance * Quality of life * Survival analysis * Clustering * Safety and efficacy assessment * Clinical design * Models for the environment * Genomic analysis * Animal health This comprehensive volume will be highly useful an of great interest to the health science community as well as practitioners, researchers, and graduate students in applied probability, statistics, and biostatistics. Nota de contenido: Prognostic Studies and General Epidemiology -- Systematic Review of Multiple Studies of Prognosis: The Feasibility of Obtaining Individual Patient Data -- On Statistical Approaches for the Multivariable Analysis of Prognostic Marker Studies -- Where Next for Evidence Synthesis of Prognostic Marker Studies? Improving the Quality and Reporting of Primary Studies to Facilitate Clinically Relevant Evidence-Based Results -- Pharmacovigilance -- Sentinel Event Methods for Monitoring Unanticipated Adverse Events -- Spontaneous Reporting System Modelling for the Evaluation of Automatic Signal Generation Methods in Pharmacovigilance -- Quality of Life -- Latent Covariates in Generalized Linear Models: A Rasch Model Approach -- Sequential Analysis of Quality of Life Measurements with the Mixed Partial Credit Model -- A Parametric Degradation Model Used in Reliability, Survival Analysis, and Quality of Life -- Agreement Between Two Ratings with Different Ordinal Scales -- Survival Analysis -- The Role of Correlated Frailty Models in Studies of Human Health, Ageing, and Longevity -- Prognostic Factors and Prediction of Residual Survival for Hospitalized Elderly Patients -- New Models and Methods for Survival Analysis of Experimental Data -- Uniform Consistency for Conditional Lifetime Distribution Estimators Under Random Right-Censorship -- Sequential Estimation for the Semiparametric Additive Hazard Model -- Variance Estimation of a Survival Function with Doubly Censored Failure Time Data -- Clustering -- Statistical Models and Artificial Neural Networks: Supervised Classification and Prediction Via Soft Trees -- Multilevel Clustering for Large Databases -- Neural Networks: An Application for Predicting Smear Negative Pulmonary Tuberculosis -- Assessing Drug Resistance in HIV Infection Using Viral Load Using Segmented Regression -- Assessment of Treatment Effects on HIV Pathogenesis Under Treatment By State Space Models -- Safety and Efficacy Assessment -- Safety Assessment Versus Efficacy Assessment -- Cancer Clinical Trials with Efficacy and Toxicity Endpoints: A Simulation Study to Compare Two Nonparametric Methods -- Safety Assessment in Pilot Studies When Zero Events Are Observed -- Clinical Designs -- An Assessment of Up-and-Down Designs and Associated Estimators in Phase I Trials -- Design of Multicentre Clinical Trials with Random Enrolment -- Statistical Methods for Combining Clinical Trial Phases II And III -- SCPRT: A Sequential Procedure That Gives Another Reason to Stop Clinical Trials Early -- Models for the Environment -- Seasonality Assessment for Biosurveillance Systems -- Comparison of Three Convolution Prior Spatial Models for Cancer Incidence -- Longitudinal Analysis of Short-Term Bronchiolitis Air Pollution Association Using Semiparametric Models -- Genomic Analysis -- Are There Correlated Genomic Substitutions? -- Animal Health -- Swiss Federal Veterinary Office Risk Assessments: Advantages and Limitations of The Qualitative Method -- Qualitative Risk Analysis in Animal Health: A Methodological Example En línea: http://dx.doi.org/10.1007/978-0-8176-4542-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34547 Ejemplares
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Título : Arts, Sciences, and Economics : A Historical Safari Tipo de documento: documento electrónico Autores: Puu, Tönu ; SpringerLink (Online service) Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2015 Otro editor: Imprint: Springer Número de páginas: XXIV, 189 p. 80 illus., 53 illus. in color Il.: online resource ISBN/ISSN/DL: 978-3-662-44130-5 Idioma : Inglés (eng) Palabras clave: Arts Cultural heritage Mathematics Social sciences Statistical physics Economics Management science Culture - Economic aspects Economics, general Heritage in the Humanities and Sciences Nonlinear Dynamics Clasificación: 316.722 Cultura de diferentes sociedades. Civilización Resumen: This book deals with the economic aspects of changing attitudes in arts and sciences. The effects of the public good character of culture, along with the very long production period and lifetime for its products, are emphasized, since both contribute to the failure of normal market solutions. Embodiment of ideas, and the consequences of modern reproduction technology for protection of property rights are closely examined. The evolution within arts and sciences, which often seems to return to previously scrapped ideals, is illustrated by detailed case studies, in which the importance of changing tastes, rather than progress proper, is emphasized. The author attempts an understanding for this using Darwinian evolution in combination with modern mathematical complexity theory, expressed in terms accessible to the general reader. The second edition is extended and updated especially as regards the illustration material. “Professor Puu (…) introduces a fourth approach [to cultural economics]. (…) working it like a triangle, Arts, Sciences and Economics is, in a sense, inductive in nature. An observation made in one of the arts or the natural & engineering sciences (henceforth ‘sciences’) or economics is extended to cover the other two points of the triangle. The temporal plane of this triangle covers the pre-Renaissance to the 21st century with a special and loving emphasis on the Baroque.(...) Professor Puu’s method reminds me of Pascal’s Pensées (…), it also reminds me of Goethe (…) Unlike Goethe, however, the ‘certain order’ achieved by Professor Puu is mathematical rather than intuitive or aesthetic in nature. Underpinning the text is the correlation between Arts, Sciences and Economics through mathematics. And mathematics covers the waterfront from probability to chaos theory (…) This underpinning does, however, reveal Professor Puu as having a very well developed mathematical mind (…). Similarly, his cultural and historical erudition cannot be faulted but rather must be praised. The text is rich in example. (…) This book is not a narrative with a beginning, middle and end. It is Professor Puu’s Pensées. (…) Calculatory rationalism is not the only tool of economics. Arguably, this is one implication of the term ‘knowledge-based economy’. To such an economy, however, Professor Puu has made a most valuable and fascinating contribution.“(...) Harry Hillman Chartrand, Book Review in Journal of Cultural Economics, vol. 31, number 1, 2007 Nota de contenido: Culture and Civilization -- Public Goods -- Patronage -- Changing Attitudes -- Evolution in Science -- Perfection in Art -- Modelling Evolution Through Structural Change En línea: http://dx.doi.org/10.1007/978-3-662-44130-5 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=35769 Arts, Sciences, and Economics : A Historical Safari [documento electrónico] / Puu, Tönu ; SpringerLink (Online service) . - Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2015 . - XXIV, 189 p. 80 illus., 53 illus. in color : online resource.
ISBN : 978-3-662-44130-5
Idioma : Inglés (eng)
Palabras clave: Arts Cultural heritage Mathematics Social sciences Statistical physics Economics Management science Culture - Economic aspects Economics, general Heritage in the Humanities and Sciences Nonlinear Dynamics Clasificación: 316.722 Cultura de diferentes sociedades. Civilización Resumen: This book deals with the economic aspects of changing attitudes in arts and sciences. The effects of the public good character of culture, along with the very long production period and lifetime for its products, are emphasized, since both contribute to the failure of normal market solutions. Embodiment of ideas, and the consequences of modern reproduction technology for protection of property rights are closely examined. The evolution within arts and sciences, which often seems to return to previously scrapped ideals, is illustrated by detailed case studies, in which the importance of changing tastes, rather than progress proper, is emphasized. The author attempts an understanding for this using Darwinian evolution in combination with modern mathematical complexity theory, expressed in terms accessible to the general reader. The second edition is extended and updated especially as regards the illustration material. “Professor Puu (…) introduces a fourth approach [to cultural economics]. (…) working it like a triangle, Arts, Sciences and Economics is, in a sense, inductive in nature. An observation made in one of the arts or the natural & engineering sciences (henceforth ‘sciences’) or economics is extended to cover the other two points of the triangle. The temporal plane of this triangle covers the pre-Renaissance to the 21st century with a special and loving emphasis on the Baroque.(...) Professor Puu’s method reminds me of Pascal’s Pensées (…), it also reminds me of Goethe (…) Unlike Goethe, however, the ‘certain order’ achieved by Professor Puu is mathematical rather than intuitive or aesthetic in nature. Underpinning the text is the correlation between Arts, Sciences and Economics through mathematics. And mathematics covers the waterfront from probability to chaos theory (…) This underpinning does, however, reveal Professor Puu as having a very well developed mathematical mind (…). Similarly, his cultural and historical erudition cannot be faulted but rather must be praised. The text is rich in example. (…) This book is not a narrative with a beginning, middle and end. It is Professor Puu’s Pensées. (…) Calculatory rationalism is not the only tool of economics. Arguably, this is one implication of the term ‘knowledge-based economy’. To such an economy, however, Professor Puu has made a most valuable and fascinating contribution.“(...) Harry Hillman Chartrand, Book Review in Journal of Cultural Economics, vol. 31, number 1, 2007 Nota de contenido: Culture and Civilization -- Public Goods -- Patronage -- Changing Attitudes -- Evolution in Science -- Perfection in Art -- Modelling Evolution Through Structural Change En línea: http://dx.doi.org/10.1007/978-3-662-44130-5 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=35769 Ejemplares
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