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  • 1
    Call number: AWI S2-07-0030
    Type of Medium: Monograph available for loan
    Pages: IX, 221 Seiten , Illustrationen
    ISBN: 9783540377054
    Series Statement: Springer-Lehrbuch
    Language: German
    Note: Inhalt: 1 Einleitung. - 1.1 Alltägliche Probleme. - 1.2 Uni- und multivariate Daten. - 1.3 Wege ins Statistiklabyrinth. - 2 Statistische Grundlagen. - 2.1 Einführung in die Terminologie. - 2.2 Datentypen -Skalenniveaus. - 2.3 Korrelation. - 2.4 Regression. - 2.5 Lineare Regression. - 2.6 Multiplelineare Regression. - 2.7 Unimodale Modelle - die Gauß'sche Regression. - 2.8 Logistische und Gauß'sche logistische Regression. - 2.9 Interaktionen. - 2.10 Gewichtetes Mittel. - 2.11 Partielle Analysen. - 3 Datenmanipulationen. - 3.1 Normalverteilung und Transformationen. - 3.2 Standardisierungen. - 3.3 Transponieren, Umkodieren und Maskieren. - 4 Ähnlichkeits- und Distanzmaße. - 4.1 Qualitative Ähnlichkeitsmaße. - 4.2 Quantitative Ähnlichkeitsmaße. - 4.3 Distanzmaße. - 4.4 Vergleich der geschilderten Koeffizienten. - 5 Ordinationen - das Prinzip. - 5.1 Dimensionsreduktion als Analysestrategie. - 5.2 Polare Ordination. - 6 Korrespondenzanalyse (CA). - 6.1 Das Prinzip. - 6.2 Mathematische Artefakte - Probleme der CA. - 6.3 DCA {Detrended Correspondence Analysis). - 6.4 Zusammenfassendes zu Problemen der CA und DCA. - 7 Interpretation von CA und DCA. - 7.1 Zur Skalierung und Interpretation der Ordinationsdiagramme. - 7.2 Umweltvariablen-Interaktionen von Effekten. - 7.3 Ordination und Umweltdaten. - 8 Kanonische Ordination (constrained ordination). - 8.1 Prinzip der Kanonischen Korrespondenzanalyse (CCA). - 8.2 Interpretation eines CCA-Diagramms. - 8.3 Forward selection bei kanonischen Ordinationen. - 8.4 Überprüfung einer CCA. - 9 Hauptkomponentenanalyse (PCA). - 9.1 Das Prinzip - geometrische Herleitung. - 9.2 Das Prinzip - der mathematische Ansatz. - 9.3 Optionen bei einer PCA. - 9.4 Stärken und Schwächen der PCA. - 9.5 Faktorenanalyse. - 10 Lineare Methoden und Umweltdaten: PCA und RDA. - 10.1 Indirekte Ordination. - 10.2 Kanonische Ordination - Prinzip der Redundanzanalyse. - 10.3 Interpretation einer RDA. - 11 Partielle Ordination und variance partitioning. - 11.1 Kovariablen. - 11.2 Partielle PCA, CA, DCA. - 11.3 Partielle kanonische Ordination. - 11.4 Variance partitioning. - 12 Multidimensionale Skalierung. - 12.1 Der andere Weg zum Ziel. - 12.2 Metrische Multidimensionale Skalierung - Hauptkoordinatenanalyse. - 12.3 Nichtmetrische Multidimensionale Skalierung. - 12.3.1 Das Prinzip. - 12.3.2 NMDS - Optionen und Probleme. - 12.3.3 Ablauf einer NMDS. - 13 Klassifikation - das Prinzip. - 13.1 Das Wesen von Klassifikationen. - 13.2 Die wichtigsten Klassifikationsstrategien. - 14 Agglomerative Klassifikationsverfahren. - 14.1Clusteranalyse - Grundlagen. - 14.2 Auswertung von Dendrogrammen. - 15 Divisive Klassifikationsverfahren. - 15.1 Ordination Space Partitioning. - 15.2 TWINSPAN. - 15.3 Ablauf einer TWINSPAN-Analyse. - 15.4 Kritik an der TWINSPAN-Analyse. - 16 Sonstige Verfahren zur Beschreibung von Gruppenstrukturen. - 16.1 Nichthierarchische agglomerative Verfahren. - 16.2 Nichthierarchische divisive Verfahren. - 16.3 Numerische "treue"-basierte Verfahren. - 16.4 Diskriminanzanalyse. - 16.4.1 Das Prinzip. - 16.4.2 Voraussetzungen. - 16.4.3 Gütekriterien/Prüfung der Ergebnisse. - 17 Permutationsbasierte Tests. - 17.1 Das Prinzip von Permutationstests. - 17.2 Test auf Signifikanz von Ordinationsachsen. - 17.3 Mantel-Test. - 17.4 Gruppenvergleiche - Mantel-Tests und MRPP. - 17.5 Procrustes-Analysen. - 17.6 Indicator Species Analysis. - 17.7 Ausblick Randomisierungsverfahren. - Literatur. - Sachverzeichnis.
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  • 2
    Call number: AWI A1-18-91747
    Description / Table of Contents: If dangerous climate change is still to be avoided, a reversal of current trends must be achieved within the next ten years, and greenhouse gas emissions worldwide must be halved by 2050 compared with a 1990 baseline. However, there is a widening gap between the action that is urgently needed and current climate policy. The German Advisory Council on Global Change (WBGU) is therefore convinced that a new climate policy dynamic is required worldwide. Currently, all eyes are on Germany: its Presidency of the Council of the European Union and Presidency of G8 offer a dual opportunity to drive climate protection forward. The Council‘s core messages are as follows: Climate protection is both worthwhile and feasible: Investing in climate protection is economically efficient, as the costs of effective climate protection are far lower than the costs of inaction. The longer we delay, the more expensive climate protection will become. For successful climate protection, a transformation of the world‘s energy systems is key. Such a transformation is technologically feasible, marking a shift away from fossil towards renewable energy sources, and requires rapid utilization of the high efficiency potentials. Further development of the UN climate convention: A consensus on the mitigation target must be forged and enshrined in the convention. To this end, the Council recommends the adoption of a global temperature guard rail limiting the rise in near-surface air temperature to a maximum of 2 °C relative to the pre-industrial value – equivalent to stabilizing the concentration of greenhouse gases below 450 ppm CO2eq. The Kyoto Protocol must be developed further and offer effective incentives for the transformation of energy systems. The industrialized countries should commit to ambitious reduction targets, while mechanisms must be established for the progressive, but differentiated integration of the newly industrializing and developing countries into commitment regimes. The issue of adaptation must also be given appropriate priority. This must include firm pledges from the industrialized countries on technological cooperation and financing. Making the most of the G8 Summit at Heiligendamm: Fresh initiatives from the heads of state and government are required to inject new life into the faltering climate process. The G8 countries and the five major newly industrializing countries, as the world‘s leading political and economic nations, should now send out clear signals and agree an ‚innovation pact on decarbonization‘. By adopting joint parameters for efficiency and CO2 emissions standards, developing a Road Atlas for the decarbonization of energy systems, and promoting technological cooperation, the G8+5 countries have the potential to become the driving force in international climate policy. Reaffirming the European Union‘s leading role: The European Union should expand its leading role in international climate protection. To maintain its credibility, it must achieve its agreed emissions reduction targets. The EU must demonstrate the viability of climate protection and provide fresh impetus for energy efficiency and renewables worldwide. The European Union‘s Emissions Trading Scheme should be developed further and improved as a matter of urgency.
    Type of Medium: Series available for loan
    Pages: 20 Seiten
    ISBN: 978-3-936191-16-6
    Series Statement: Policy paper / WBGU, German Advisory Council on Global Change 5
    Language: English
    Note: CONTENTS: Summary for Policy-Makers. - 1 Climate protection: Swift action is essential. - The scientific evidence is clear. - Compliance with the 2 °C guard rail is worthwhile. - 2 Transforming the world‘s energy systems: The cornerstone of climate protection. - The energy portfolio for the future. - A new generation of energy technologies . - Mobilizing untapped efficiency potential. - Financing the transformation of energy systems. - A new climate policy dynamic. - 3 Implementing and developing the Climate Change Convention. - Making the 2 °C guard rail an international standard. - Gearing the Kyoto Protocol towards the long term. - Agreeing ambitious reduction targets for industrialized countries. - Integrating newly industrializing countries on a differentiated basis. - Giving adaptation high priority. - 4 Agreeing an innovation pact with Road Atlas at the G8 summit. - Agreeing parameters for climate-compatible technologies. - Developing a joint Road Atlas. - Offering technological cooperation as an incentive. - Harnessing impetus for the Climate Change Convention. - 5 Strengthening the EU‘s leading role. - Triggering an efficiency revolution. - Expanding renewables. - Fostering international cooperation in the energy sector. - Making the Emission Trading Scheme efficient and effective . - Strengthening the function of the public sector as a role model. - Implementing the programme of action on ‘sustainable consumption‘. - Redirecting energy subsidies. - Boosting adaptation within the framework of development cooperation. , Deutsche Ausgabe unter dem Titel: Neue Impulse für die Klimapolitik
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  • 3
    Call number: PIK M 102-08-0153 ; PIK M 102-08-0257 ; 19/M 10.0047 ; AWI S1-10-0005
    Type of Medium: Monograph available for loan
    Pages: XII, 288 Seiten , Illustrationen, Diagramme, Karten , 1 CD-ROM (12 cm)
    Edition: Second edition
    ISBN: 3540727485 , 978-3-540-72748-4
    Language: English
    Note: Contents Preface 1 Data Analysis in Earth Sciences 1.1 Introduction 1.2 Collecting Data 1.3 Types of Data 1.4 Methods of Data Analysis Recommended Reading 2 Introduction to MATLAB 2.1 MATLAB in Earth Sciences 2.2 Getting Started 2.3 The Syntax 2.4 Data Storage 2.5 Data Handling 2.6 Scripts and Functions 2.7 Basic Visualization Tools Recommended Reading 3 Univariate Statistics 3.1 Introduction 3.2 Empirical Distributions Measures of Central Tendency Measures of Dispersion 3.3 Example of Empirical Distributions 3.4 Theoretical Distributions Uniform Distribution Binomial or Bernoulli Distribution Poisson Distribution Normal or Gaussian Distribution Logarithmic Normal or Log-Normal Distribution Student's t Distribution Fisher's F Distribution Χ2 or Chi-Squared Distribution 3.5 Example ofTheoretical Distributions 3.6 Thet-Test 3.7 TheF-Test 3.8 The Χ2-Test Recommended Reading 4 Bivariate Statistics 4.1 Introduction 4.2 Pearson's Correlation Coefficient 4.3 Classical Linear Regression Analysis and Prediction 4.4 Analyzing the Residuals 4.5 Bootstrap Estimates of the Regression Coefficients 4.6 Jackknife Estimates of the Regression Coefficients 4.7 Cross Validation 4.8 Reduced Major Axis Regression 4.9 Curvilinear Regression Recommended Reading 5 Time-Series Analysis 5.1 Introduction 5.2 Generating Signals 5.3 Blackman-Tukey Autospectral Analysis 5.4 Blackman-Tukey Crossspectral Analysis 5.5 Interpolating and Analyzing Unevenly-Spaced Data 5.6 Evolutionary Blackman-Tukey Powerspectrum 5.7 Lomb-Scargle Powerspectrum 5.8 Wavelet Powerspectrum 5.9 Nonlinear Time-Series Analysis (by N. Marwarn) Phase Space Portrait Recurrence Plots Recommended Reading 6 Signal Processing 6.1 Introduction 6.2 Generating Signals 6.3 Linear Time-Invariant Systems 6.4 Convolution and Filtering 6.5 Comparing Functions for Filtering Data Series 6.6 Recursive and Nonrecursive Filters 6.7 Impulse Response 6.8 Frequency Response 6.9 Filter Design 6.10 Adaptive Filtering Recommended Reading 7 Spatial Data 7.1 Types of Spatial Data 7.2 The GSHHS Shoreline Data Set 7.3 The 2-Minute Gridded Global Elevation Data ETOPO2 7.4 The 30-Arc Seconds Elevation Model GTOPO30 7.5 The Shuttle Radar Topography Mission SRTM 7.6 Gridding and Contouring Background 7.7 Gridding Example 7.8 Comparison of Methods and Potential Artifacts 7.9 Statistics of Point Distributions Test for Uniform Distribution Test for Random Distribution Test for Clustering 7.10 Analysis of Digital Elevation Models (by R. Gebbers) 7.11 Geostatistics and Kriging (by R. Gebbers) Theorical Background Preceding Analysis Variography with the Classical Variogram Kriging Discussion of Kriging Recommended Reading 8 Image Processing 8.1 Introduction 8.2 Datastorage 8.3 Importing, Processing and Exporting Images 8.4 Importing, Processing and Exporting Satellite Images 8.5 Georeferencing Satellite Images 8.6 Digitizing from the Screen Recommended Reading 9 Multivariate Statistics 9.1 Introduction 9.2 Principal Component Analysis 9.3 Independent Component Analysis (by N. Marwan) 9.4 Cluster Analysis Recommended Reading 10 Statistics on Directional Data 10.1 Introduction 10.2 Graphical Representation 10.3 Empirical Distributions 10.4 Theoretical Distributions 10.5 Test for Randomness of Directional Data 10.6 Test for the Significance of a Mean Direction 10.7 Test for the Difference of Two Sets of Directions Recommended Reading General Index
    Location: A 18 - must be ordered
    Location: A 18 - must be ordered
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  • 4
    Call number: 9783540377061 (e-book)
    Type of Medium: 12
    Pages: 1 Online-Ressource (IX, 221 Seiten) , Illustrationen
    Edition: Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.
    ISBN: 9783540377054 , 9783540377061
    Series Statement: Springer-Lehrbuch
    Language: German
    Note: Inhalt: 1 Einleitung. - 1.1 Alltägliche Probleme. - 1.2 Uni- und multivariate Daten. - 1.3 Wege ins Statistiklabyrinth. - 2 Statistische Grundlagen. - 2.1 Einführung in die Terminologie. - 2.2 Datentypen -Skalenniveaus. - 2.3 Korrelation. - 2.4 Regression. - 2.5 Lineare Regression. - 2.6 Multiplelineare Regression. - 2.7 Unimodale Modelle - die Gauß'sche Regression. - 2.8 Logistische und Gauß'sche logistische Regression. - 2.9 Interaktionen. - 2.10 Gewichtetes Mittel. - 2.11 Partielle Analysen. - 3 Datenmanipulationen. - 3.1 Normalverteilung und Transformationen. - 3.2 Standardisierungen. - 3.3 Transponieren, Umkodieren und Maskieren. - 4 Ähnlichkeits- und Distanzmaße. - 4.1 Qualitative Ähnlichkeitsmaße. - 4.2 Quantitative Ähnlichkeitsmaße. - 4.3 Distanzmaße. - 4.4 Vergleich der geschilderten Koeffizienten. - 5 Ordinationen - das Prinzip. - 5.1 Dimensionsreduktion als Analysestrategie. - 5.2 Polare Ordination. - 6 Korrespondenzanalyse (CA). - 6.1 Das Prinzip. - 6.2 Mathematische Artefakte - Probleme der CA. - 6.3 DCA {Detrended Correspondence Analysis). - 6.4 Zusammenfassendes zu Problemen der CA und DCA. - 7 Interpretation von CA und DCA. - 7.1 Zur Skalierung und Interpretation der Ordinationsdiagramme. - 7.2 Umweltvariablen-Interaktionen von Effekten. - 7.3 Ordination und Umweltdaten. - 8 Kanonische Ordination (constrained ordination). - 8.1 Prinzip der Kanonischen Korrespondenzanalyse (CCA). - 8.2 Interpretation eines CCA-Diagramms. - 8.3 Forward selection bei kanonischen Ordinationen. - 8.4 Überprüfung einer CCA. - 9 Hauptkomponentenanalyse (PCA). - 9.1 Das Prinzip - geometrische Herleitung. - 9.2 Das Prinzip - der mathematische Ansatz. - 9.3 Optionen bei einer PCA. - 9.4 Stärken und Schwächen der PCA. - 9.5 Faktorenanalyse. - 10 Lineare Methoden und Umweltdaten: PCA und RDA. - 10.1 Indirekte Ordination. - 10.2 Kanonische Ordination - Prinzip der Redundanzanalyse. - 10.3 Interpretation einer RDA. - 11 Partielle Ordination und variance partitioning. - 11.1 Kovariablen. - 11.2 Partielle PCA, CA, DCA. - 11.3 Partielle kanonische Ordination. - 11.4 Variance partitioning. - 12 Multidimensionale Skalierung. - 12.1 Der andere Weg zum Ziel. - 12.2 Metrische Multidimensionale Skalierung - Hauptkoordinatenanalyse. - 12.3 Nichtmetrische Multidimensionale Skalierung. - 12.3.1 Das Prinzip. - 12.3.2 NMDS - Optionen und Probleme. - 12.3.3 Ablauf einer NMDS. - 13 Klassifikation - das Prinzip. - 13.1 Das Wesen von Klassifikationen. - 13.2 Die wichtigsten Klassifikationsstrategien. - 14 Agglomerative Klassifikationsverfahren. - 14.1Clusteranalyse - Grundlagen. - 14.2 Auswertung von Dendrogrammen. - 15 Divisive Klassifikationsverfahren. - 15.1 Ordination Space Partitioning. - 15.2 TWINSPAN. - 15.3 Ablauf einer TWINSPAN-Analyse. - 15.4 Kritik an der TWINSPAN-Analyse. - 16 Sonstige Verfahren zur Beschreibung von Gruppenstrukturen. - 16.1 Nichthierarchische agglomerative Verfahren. - 16.2 Nichthierarchische divisive Verfahren. - 16.3 Numerische "treue"-basierte Verfahren. - 16.4 Diskriminanzanalyse. - 16.4.1 Das Prinzip. - 16.4.2 Voraussetzungen. - 16.4.3 Gütekriterien/Prüfung der Ergebnisse. - 17 Permutationsbasierte Tests. - 17.1 Das Prinzip von Permutationstests. - 17.2 Test auf Signifikanz von Ordinationsachsen. - 17.3 Mantel-Test. - 17.4 Gruppenvergleiche - Mantel-Tests und MRPP. - 17.5 Procrustes-Analysen. - 17.6 Indicator Species Analysis. - 17.7 Ausblick Randomisierungsverfahren. - Literatur. - Sachverzeichnis.
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