Showing results for "Statistical Methods for Astronomical Data Analysis German"
Showing 1 - 12 of 49613 Results
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2014
EN
This book introduces “Astrostatistics” as a subject in its own right with rewarding examples, including work by the authors with galaxy and Gamma Ray Burst data to engage the reader. This includes a comprehensive blending of Astrophysics and Statistics. The first chapter’s coverage of preliminary concepts and terminologies for astronomical phenomenon will appeal to both Statistics and Astrophysics readers as helpful context. Statistics concepts covered in the book provide a methodological ...
Statistical Methods for Engineers and Scientists
Applied Probability, Reliability Data, and Pattern Recognition for Machine Learning
2026
EN
Stop forcing clean textbook data onto messy engineering reality.Real engineering data arrives censored, correlated, and far from normal. Inspection records stop at the detection limit. Failure times are truncated by test schedules. Measurements carry uncertainty that propagates through every downstream calculation. Statistical Methods for Engineers and Scientists teaches inference on the data you actually have, not the idealized samples in a classroom exam...
2012
EN
The theme of the meeting was “Statistical Methods for the Analysis of Large Data-Sets”. In recent years there has been increasing interest in this subject; in fact a huge quantity of information is often available but standard statistical techniques are usually not well suited to managing this kind of data. The conference serves as an important meeting point for European researchers working on this topic and a number of European statistical societies participated in the organization of the...
Data Analysis
Statistical and Computational Methods for Scientists and Engineers
- Series -
- Physics and Astronomy (R0)
2014
EN
The fourth edition of this successful textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Equal weight is given to statistical theory and practical problems. The concise mathematical treatment of the subject matter is illustrated by many examples and for the present edition a library of Java programs has been developed. It comprises methods of numerical data analysis and graphical representation as well ...
Data Science and Machine Learning
Mathematical and Statistical Methods, Second Edition
2025
EN
Praise for the first edition:“In nine succinct but information-packed chapters, the authors provide a logically structured and robust introduction to the mathematical and statistical methods underpinning the still-evolving field of AI and data science.”- Joacim Rocklöv and Albert A. Gayle, International Journal of Epidemiology, Volume 49, Issue 6“This book organizes the algorithms clearly and cleverly. The way the Python code was written follows the algorit...
2013
EN
The papers in this book cover issues related to the development of novel statistical models for the analysis of data. They offer solutions for relevant problems in statistical data analysis and contain the explicit derivation of the proposed models as well as their implementation. The book assembles the selected and refereed proceedings of the biannual conference of the Italian Classification and Data Analysis Group (CLADAG), a section of the Italian Statistical Society.
Statistical Analysis for Beginners
Comprehensive Introduction
- Book 2 -
- Data Analysis 3 in 1
2026
EN
Dive into the fascinating realm of data with "Statistical Analysis for Beginners: A Hands-On Approach to Unraveling Data Mysteries and Transforming Numbers into Knowledge." This comprehensive guide is crafted for those seeking to demystify the world of statistics and harness the power of data in their hands. Unlock the Secrets of Numbers: Embark on a journey that transforms raw data into valuable insights. This book introduces beginners to the fundamental concept...
Statistical Learning and Modeling in Data Analysis
Methods and Applications
2021
EN
The contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series of engaging real-world applications. The book covers numerous research topics, ranging from statistical inference and modeling to clustering and factorial methods, from directional data analysis to time series analysis and small area estimation. The applications reflect new analyses in a variety of fields, including medicine, finance, engineering, mark...
2013
EN
This thesis explores advanced Bayesian statistical methods for extracting key information for cosmological model selection, parameter inference and forecasting from astrophysical observations. Bayesian model selection provides a measure of how good models in a set are relative to each other - but what if the best model is missing and not included in the set? Bayesian Doubt is an approach which addresses this problem and seeks to deliver an absolute rather than a relative measure of how goo...
2025
EN
Accessible
This book on statistical models and learning methods for complex data comprises a selection of peer-reviewed post-conference papers presented at the 14th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2023), held in Salerno, Italy, September 11–13, 2023. The contributions span a variety of topics, including different approaches to clustering and classification, multidimensional data analysis, panel data, social networks, time ser...
2023
EN
This book focuses on methods and models in classification and data analysis and presents real-world applications at the interface with data science. Numerous topics are covered, ranging from statistical inference and modelling to clustering and factorial methods, and from directional data analysis to time series analysis and small area estimation. The applications deal with new developments in a variety of fields, including medicine, finance, engineering, marketing, and cyber risk....
2015
EN
This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG)...











