Environmental Data Analysis With Matlab Or Python - Principles, Applications, and Prospects

Previous edition: published as by William Menke, Joshua Menke. 2016.

Sommario

1. Data Analysis with MATLAB or Python 2. Systematic explorations of a new dataset 3. Modeling observational noise with random variables 4. Linear models as the foundation of data analysis 5. Least squares with prior information 6. Detecting periodicities with Fourier analysis 7. Modeling time-dependent behavior with filters 8. Undirected data analysis using factors, empirical orthogonal functions and clusters 9. Detecting and understanding correlations among data 10. Interpolation, Gaussian Process Regression and Kriging 11. Approximate methods, including linearization and artificial neural networks 12. Assessing the significance of results

Info autore

William Menke is a Professor of Earth and Environmental Sciences at Columbia University. His research focuses on the development of data analysis algorithms for time series analysis and imaging in the earth and environmental sciences and the application of these methods to volcanoes, earthquakes, and other natural hazards. He has thirty years of experience teaching data analysis methods to both undergraduates and graduate students. Relevant courses that he has taught include, at the undergraduate level, Environmental Data Analysis and The Earth System, and at the graduate level, Geophysical Inverse Theory, Quantitative Methods of Data Analysis, Geophysical Theory and Practical Seismology.

Dettagli sul prodotto

• Autori: William Menke, William (Professor Menke, William (Professor of Earth and Environment Menke, William (Professor of Earth and Environmental Sciences Menke, Menke William
• Editore: ELSEVIER SCIENCE BV
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 31.08.2022
• EAN: 9780323955768
• ISBN: 978-0-323-95576-8
• Pagine: 466
• Categorie: Scienze naturali, medicina, informatica, tecnica > Biologia > Ecologia; SCIENCE / Research & Methodology, The environment, Science / Environmental Science, Stochastics, Environmental Monitoring, Environmental science, engineering and technology, Scientific research