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Statistical Physics: An Advanced Approach with Applications

Posted By: AvaxGenius
Statistical Physics: An Advanced Approach with Applications

Statistical Physics: An Advanced Approach with Applications by Josef Honerkamp
English | PDF | 1998 | 416 Pages | ISBN : 3540639780 | 32.1 MB

The application of statistical methods to physics is essential. This unique book on statistical physics offers an advanced approach with numerous applications to the modern problems students are confronted with. Therefore the text contains more concepts and methods in statistics than the student would needed for statistical mechanics alone. Methods from mathematical statistics and stochastics for the analysis of data are discussed as well. The book is divided in two parts focusing first on the modelling of statistical systems then on the analysis of these systems. Problems with hints for solution help the students to deepen their knowledge.

40 Puzzles and Problems in Probability and Mathematical Statistics

Posted By: AvaxGenius
40 Puzzles and Problems in Probability and Mathematical Statistics

40 Puzzles and Problems in Probability and Mathematical Statistics by Wolf Schwarz
English | PDF(True) | 2008 | 135 Pages | ISBN : 0387735119 | 2.2 MB

"40 Puzzles and Problems in Probability and Mathematical Statistics" is intended to teach the reader to think probabilistically by solving challenging, non-standard probability problems. The motivation for this clearly written collection lies in the belief that challenging problems help to develop, and to sharpen, our probabilistic intuition much better than plain-style deductions from abstract concepts. The selected problems fall into two broad categories. Problems related to probability theory come first, followed by problems related to the application of probability to the field of mathematical statistics. All problems seek to convey a non-standard aspect or an approach which is not immediately obvious.

Statistical Data Modeling and Machine Learning with Applications

Posted By: AvaxGenius
Statistical Data Modeling and Machine Learning with Applications

Statistical Data Modeling and Machine Learning with Applications by Snezhana Gocheva-Ilieva
English | PDF | 2021 | 186 Pages | ISBN : 3036526927 | 11.5 MB

The modeling and processing of empirical data is one of the main subjects and goals of statistics. Nowadays, with the development of computer science, the extraction of useful and often hidden information and patterns from data sets of different volumes and complex data sets in warehouses has been added to these goals. New and powerful statistical techniques with machine learning (ML) and data mining paradigms have been developed.

Large Sample Techniques for Statistics (Repost)

Posted By: AvaxGenius
Large Sample Techniques for Statistics (Repost)

Large Sample Techniques for Statistics by Jiming Jiang
English | PDF | 2010 | 611 Pages | ISBN : 1441968261 | 4.6 MB

This book offers a comprehensive guide to large sample techniques in statistics. More importantly, it focuses on thinking skills rather than just what formulae to use; it provides motivations, and intuition, rather than detailed proofs; it begins with very simple techniques, and connects theory and applications in entertaining ways.

Asymptotics in Statistics: Some Basic Concepts

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Asymptotics in Statistics: Some Basic Concepts

Asymptotics in Statistics: Some Basic Concepts by Lucien Le Cam
English | PDF | 2000 | 299 Pages | ISBN : 1461270308 | 24.8 MB

by Sara van de Geer. Also, we did not include material due to David Donoho, lain Johnstone, and their school. We found our­ selves unprepared to write a distillate of the material. We did touch briefly on "nonparametrics," but not on "semiparamet­ rics." This is because we feel that the semiparametric situation has not yet been properly structured.

Fundamentals of Mathematical Statistics: Probability for Statistics

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Fundamentals of Mathematical Statistics: Probability for Statistics

Fundamentals of Mathematical Statistics: Probability for Statistics by Hung T. Nguyen
English | PDF | 1989 | 442 Pages | ISBN : 1461269849 | 13.9 MB

This is the first half of a text for a two semester course in mathematical statistics at the senior/graduate level for those who need a strong background in statistics as an essential tool in their career.

Probabilistic and Statistical Aspects of Quantum Theory (Repost)

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Probabilistic and Statistical Aspects of Quantum Theory (Repost)

Probabilistic and Statistical Aspects of Quantum Theory by Alexander Holevo
English | PDF | 2011 | 336 Pages | ISBN : 8876423753 | 1.88 MB

This book is devoted to aspects of the foundations of Quantum Mechanics in which probabilistic and statistical concepts play an essential role. The main part of the book concerns the quantitative statistical theory of quantum measurement, based on the notion of Positive Operator-valued Measures.

Statistical Challenges in Modern Astronomy II

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Statistical Challenges in Modern Astronomy II

Statistical Challenges in Modern Astronomy II by G. Jogesh Babu
English | PDF | 1997 | 463 Pages | ISBN : 1461273609 | 42 MB

Modern astronomical research faces a vast range of statistical issues which have spawned a revival in methodological activity among astronomers. The Statistical Challenges in Modern Astronomy II conference, held in June 1996 at the Pennsylvania State University five years after the first conference, brought astronomers and statisticians together to discuss methodological issues of common interest. Time series analysis, image analysis, Bayesian methods, Poisson processes, nonlinear regression, maximum likelihood, multivariate classification, and wavelet and multiscale analyses were important themes.

Foundations of Statistical Analyses and Applications with SAS

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Foundations of Statistical Analyses and Applications with SAS

Foundations of Statistical Analyses and Applications with SAS by Michael Falk
English | PDF | 2002 | 405 Pages | ISBN : 0817668934 | 38.48 MB

The analysis of real data by means of statistical methods with the aid of a software package common in industry and administration will certainly be part of a future professional work of many students in mathematics or mathematical statistics.