Statistics in Musicology

Author: Jan Beran
Publisher: CRC Press
ISBN: 1135442495
Format: PDF, Mobi
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Traditionally, statistics and music are not generally associated with each other. However, ...intelligent... music software, computer digitization, and other advanced techniques and technologies have precipitated the need for standard statistical models to answer basic musicological questions. Statistics In Musicology presents an unprecedented introduction to statistical and mathematical methods developed for use in music analysis, music theory, and performance theory. It explores concrete methods for data generation and numerical encoding of musical data and serves as a practical reference for a wide audience, including statisticians, mathematicians, musicologists, and musicians.

Statistics in Musicology

Author: Jan Beran
Publisher: CRC Press
ISBN: 0203496949
Format: PDF, Docs
Download Now
Traditionally, statistics and music are not generally associated with each other. However, ...intelligent... music software, computer digitization, and other advanced techniques and technologies have precipitated the need for standard statistical models to answer basic musicological questions. Statistics In Musicology presents an unprecedented introduction to statistical and mathematical methods developed for use in music analysis, music theory, and performance theory. It explores concrete methods for data generation and numerical encoding of musical data and serves as a practical reference for a wide audience, including statisticians, mathematicians, musicologists, and musicians.

A Theory of Music Analysis

Author: Dora A. Hanninen
Publisher: University Rochester Press
ISBN: 1580461948
Format: PDF, Kindle
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This book introduces a theory of music analysis--a language and conceptual framework--that analysts can use to delve into aspects of segmentation and associative organization in a wide range of repertoire from the Baroque to the present. Rather than a methodology, the theory provides analysts with a precise language and broad, flexible conceptual framework that they can when formulating and investigating questions of interest and develop their own interpretations of individual pieces and passages. The theory begins with a basic distinction among three domains of musical experience and discourse about it: the sonic (psychoacoustic); the contextual (or associative, sparked by varying degrees of repetition); and the structural (guided by a specific theory of musical structure or syntax invoked by the analyst). A comprehensive presentation of the theory (with copious musical illustrations) is balanced with close analyses of works by Beethoven, Debussy, Nancarrow, Riley, Feldman, and Morris -- Publisher summary.

Statistics of Medical Imaging

Author: Tianhu Lei
Publisher: CRC Press
ISBN: 1420088432
Format: PDF, Kindle
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Statistical investigation into technology not only provides a better understanding of the intrinsic features of the technology (analysis), but also leads to an improved design of the technology (synthesis). Physical principles and mathematical procedures of medical imaging technologies have been extensively studied during past decades. However, less work has been done on the statistical aspects of these techniques. Statistics of Medical Imaging fills this gap and provides a theoretical framework for statistical investigation into medical imaging technologies. Features Describes physical principles and mathematical procedures of two medical imaging techniques: X-ray CT and MRI Presents statistical properties of imaging data (measurements) at each stage in the imaging processes of X-ray CT and MRI Demonstrates image reconstruction as a transform from a set of random variables (imaging data) to another set of random variables (image data) Presents statistical properties of image data (pixel intensities) at three levels: a single pixel, any two pixels, and a group of pixels (a region) Provides two stochastic models for X-ray CT and MR image in terms of their statistics and two model-based statistical image analysis methods Evaluates statistical image analysis methods in terms of their detection, estimation, and classification performances Indicates that X-ray CT, MRI, PET and SPECT belong to a category of imaging: the non-diffraction computed tomography Rather than offering detailed descriptions of statistics of basic imaging protocols of X-ray CT and MRI, this book provides a method to conduct similar statistical investigations into more complicated imaging protocols.

Statistical Concepts and Applications in Clinical Medicine

Author: John Aitchison
Publisher: CRC Press
ISBN: 0203497414
Format: PDF
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Statistical Concepts and Applications in Clinical Medicine presents a unique, problem-oriented approach to using statistical methods in clinical medical practice through each stage of the clinical process, including observation, diagnosis, and treatment. The authors present each consultative problem in its original form, then describe the process of problem formulation, develop the appropriate statistical models, and interpret the statistical analysis in the context of the real problem. Their treatment provides clear, accessible explanations of statistical methods. The text includes end-of-chapter exercises that help develop formulatory, analytic, and interpretative skills.

Measurement Error and Misclassification in Statistics and Epidemiology

Author: Paul Gustafson
Publisher: CRC Press
ISBN: 0203502760
Format: PDF, Docs
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Mismeasurement of explanatory variables is a common hazard when using statistical modeling techniques, and particularly so in fields such as biostatistics and epidemiology where perceived risk factors cannot always be measured accurately. With this perspective and a focus on both continuous and categorical variables, Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments examines the consequences and Bayesian remedies in those cases where the explanatory variable cannot be measured with precision. The author explores both measurement error in continuous variables and misclassification in discrete variables, and shows how Bayesian methods might be used to allow for mismeasurement. A broad range of topics, from basic research to more complex concepts such as "wrong-model" fitting, make this a useful research work for practitioners, students and researchers in biostatistics and epidemiology."

Computational Musicology in Hindustani Music

Author: Soubhik Chakraborty
Publisher: Springer
ISBN: 3319114727
Format: PDF, ePub, Docs
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The book opens with a short introduction to Indian music, in particular classical Hindustani music, followed by a chapter on the role of statistics in computational musicology. The authors then show how to analyze musical structure using Rubato, the music software package for statistical analysis, in particular addressing modeling, melodic similarity and lengths, and entropy analysis; they then show how to analyze musical performance. Finally, they explain how the concept of seminatural composition can help a music composer to obtain the opening line of a raga-based song using Monte Carlo simulation. The book will be of interest to musicians and musicologists, particularly those engaged with Indian music.

Statistical and Probabilistic Methods in Actuarial Science

Author: Philip J. Boland
Publisher: CRC Press
ISBN: 158488696X
Format: PDF, Kindle
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Statistical and Probabilistic Methods in Actuarial Science covers many of the diverse methods in applied probability and statistics for students aspiring to careers in insurance, actuarial science, and finance. The book builds on students’ existing knowledge of probability and statistics by establishing a solid and thorough understanding of these methods. It also emphasizes the wide variety of practical situations in insurance and actuarial science where these techniques may be used. Although some chapters are linked, several can be studied independently from the others. The first chapter introduces claims reserving via the deterministic chain ladder technique. The next few chapters survey loss distributions, risk models in a fixed period of time, and surplus processes, followed by an examination of credibility theory in which collateral and sample information are brought together to provide reasonable methods of estimation. In the subsequent chapter, experience rating via no claim discount schemes for motor insurance provides an interesting application of Markov chain methods. The final chapters discuss generalized linear models and decision and game theory. Developed by an author with many years of teaching experience, this text presents an accessible, sound foundation in both the theory and applications of actuarial science. It encourages students to use the statistical software package R to check examples and solve problems.

Empirical Musicology

Author: Eric Clarke
Publisher: Oxford University Press
ISBN: 019516749X
Format: PDF, Kindle
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Rather than advocating a new kind of musicology, 'Empirical Musicology' aims to provide a practical guide to empirical approaches that are ready for incorporation into the contemporary musicologist's toolkit.

Music Data Mining

Author: Tao Li
Publisher: CRC Press
ISBN: 1439835527
Format: PDF
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The research area of music information retrieval has gradually evolved to address the challenges of effectively accessing and interacting large collections of music and associated data, such as styles, artists, lyrics, and reviews. Bringing together an interdisciplinary array of top researchers, Music Data Mining presents a variety of approaches to successfully employ data mining techniques for the purpose of music processing. The book first covers music data mining tasks and algorithms and audio feature extraction, providing a framework for subsequent chapters. With a focus on data classification, it then describes a computational approach inspired by human auditory perception and examines instrument recognition, the effects of music on moods and emotions, and the connections between power laws and music aesthetics. Given the importance of social aspects in understanding music, the text addresses the use of the Web and peer-to-peer networks for both music data mining and evaluating music mining tasks and algorithms. It also discusses indexing with tags and explains how data can be collected using online human computation games. The final chapters offer a balanced exploration of hit song science as well as a look at symbolic musicology and data mining. The multifaceted nature of music information often requires algorithms and systems using sophisticated signal processing and machine learning techniques to better extract useful information. An excellent introduction to the field, this volume presents state-of-the-art techniques in music data mining and information retrieval to create novel ways of interacting with large music collections.