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Alexander Kniazev Introduction to Bayesian - prodevochek.ru
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Ioannis Ntzoufras Bayesian Modeling Using WinBUGS


A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using WinBUGS provides an easily accessible introduction to the use of WinBUGS programming techniques in a variety of Bayesian modeling settings. The author provides an accessible treatment of the topic, offering readers a smooth introduction to the principles of Bayesian modeling with detailed guidance on the practical implementation of key principles. The book begins with a basic introduction to Bayesian inference and the WinBUGS software and goes on to cover key topics, including: Markov Chain Monte Carlo algorithms in Bayesian inference Generalized linear models Bayesian hierarchical models Predictive distribution and model checking Bayesian model and variable evaluation Computational notes and screen captures illustrate the use of both WinBUGS as well as R software to apply the discussed techniques. Exercises at the end of each chapter allow readers to test their understanding of the presented concepts and all data sets and code are available on the book's related Web site. Requiring only a working knowledge of probability theory and statistics, Bayesian Modeling Using WinBUGS serves as an excellent book for courses on Bayesian statistics at the upper-undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners in the fields of statistics, actuarial science, medicine, and the social sciences who use WinBUGS in their everyday work.

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Alexander Kniazev Introduction to Bayesian Estimation and Copula Models of Dependence


Presents an introduction to Bayesian statistics, presents an emphasis on Bayesian methods (prior and posterior), Bayes estimation, prediction, MCMC,Bayesian regression, and Bayesian analysis of statistical modelsof dependence, and features a focus on copulas for risk management Introduction to Bayesian Estimation and Copula Models of Dependence emphasizes the applications of Bayesian analysis to copula modeling and equips readers with the tools needed to implement the procedures of Bayesian estimation in copula models of dependence. This book is structured in two parts: the first four chapters serve as a general introduction to Bayesian statistics with a clear emphasis on parametric estimation and the following four chapters stress statistical models of dependence with a focus of copulas. A review of the main concepts is discussed along with the basics of Bayesian statistics including prior information and experimental data, prior and posterior distributions, with an emphasis on Bayesian parametric estimation. The basic mathematical background of both Markov chains and Monte Carlo integration and simulation is also provided. The authors discuss statistical models of dependence with a focus on copulas and present a brief survey of pre-copula dependence models. The main definitions and notations of copula models are summarized followed by discussions of real-world cases that address particular risk management problems. In addition, this book includes: • Practical examples of copulas in use including within the Basel Accord II documents that regulate the world banking system as well as examples of Bayesian methods within current FDA recommendations • Step-by-step procedures of multivariate data analysis and copula modeling, allowing readers to gain insight for their own applied research and studies • Separate reference lists within each chapter and end-of-the-chapter exercises within Chapters 2 through 8 • A companion website containing appendices: data files and demo files in Microsoft® Office Excel®, basic code in R, and selected exercise solutions Introduction to Bayesian Estimation and Copula Models of Dependence is a reference and resource for statisticians who need to learn formal Bayesian analysis as well as professionals within analytical and risk management departments of banks and insurance companies who are involved in quantitative analysis and forecasting. This book can also be used as a textbook for upper-undergraduate and graduate-level courses in Bayesian statistics and analysis. ARKADY SHEMYAKIN, PhD, is Professor in the Department of Mathematics and Director of the Statistics Program at the University of St. Thomas. A member of the American Statistical Association and the International Society for Bayesian Analysis, Dr. Shemyakin's research interests include informationtheory, Bayesian methods of parametric estimation, and copula models in actuarial mathematics, finance, and engineering. ALEXANDER KNIAZEV, PhD, is Associate Professor and Head of the Department of Mathematics at Astrakhan State University in Russia. Dr. Kniazev's research interests include representation theory of Lie algebras and finite groups, mathematical statistics, econometrics, and financial mathematics.

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William Bolstad M. Introduction to Bayesian Statistics


"…this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels. It is a well-written book on elementary Bayesian inference, and the material is easily accessible. It is both concise and timely, and provides a good collection of overviews and reviews of important tools used in Bayesian statistical methods." There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian statistics. The authors continue to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inference for discrete random variables, binomial proportions, Poisson, and normal means, and simple linear regression. In addition, more advanced topics in the field are presented in four new chapters: Bayesian inference for a normal with unknown mean and variance; Bayesian inference for a Multivariate Normal mean vector; Bayesian inference for the Multiple Linear Regression Model; and Computational Bayesian Statistics including Markov Chain Monte Carlo. The inclusion of these topics will facilitate readers' ability to advance from a minimal understanding of Statistics to the ability to tackle topics in more applied, advanced level books. Minitab macros and R functions are available on the book's related website to assist with chapter exercises. Introduction to Bayesian Statistics, Third Edition also features: Topics including the Joint Likelihood function and inference using independent Jeffreys priors and join conjugate prior The cutting-edge topic of computational Bayesian Statistics in a new chapter, with a unique focus on Markov Chain Monte Carlo methods Exercises throughout the book that have been updated to reflect new applications and the latest software applications Detailed appendices that guide readers through the use of R and Minitab software for Bayesian analysis and Monte Carlo simulations, with all related macros available on the book's website Introduction to Bayesian Statistics, Third Edition is a textbook for upper-undergraduate or first-year graduate level courses on introductory statistics course with a Bayesian emphasis. It can also be used as a reference work for statisticians who require a working knowledge of Bayesian statistics.

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Cameletti Michela Spatial and Spatio-temporal Bayesian Models with R - INLA


Spatial and Spatio-Temporal Bayesian Models with R-INLA provides a much needed, practically oriented & innovative presentation of the combination of Bayesian methodology and spatial statistics. The authors combine an introduction to Bayesian theory and methodology with a focus on the spatial and spatio­-temporal models used within the Bayesian framework and a series of practical examples which allow the reader to link the statistical theory presented to real data problems. The numerous examples from the fields of epidemiology, biostatistics and social science all are coded in the R package R-INLA, which has proven to be a valid alternative to the commonly used Markov Chain Monte Carlo simulations

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Simon Jackman Bayesian Analysis for the Social Sciences


Bayesian methods are increasingly being used in the social sciences, as the problems encountered lend themselves so naturally to the subjective qualities of Bayesian methodology. This book provides an accessible introduction to Bayesian methods, tailored specifically for social science students. It contains lots of real examples from political science, psychology, sociology, and economics, exercises in all chapters, and detailed descriptions of all the key concepts, without assuming any background in statistics beyond a first course. It features examples of how to implement the methods using WinBUGS – the most-widely used Bayesian analysis software in the world – and R – an open-source statistical software. The book is supported by a Website featuring WinBUGS and R code, and data sets.

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Peter Lee M. Bayesian Statistics. An Introduction


Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques. This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as well as how it contrasts with the conventional approach. The theory is built up step by step, and important notions such as sufficiency are brought out of a discussion of the salient features of specific examples. This edition: Includes expanded coverage of Gibbs sampling, including more numerical examples and treatments of OpenBUGS, R2WinBUGS and R2OpenBUGS. Presents significant new material on recent techniques such as Bayesian importance sampling, variational Bayes, Approximate Bayesian Computation (ABC) and Reversible Jump Markov Chain Monte Carlo (RJMCMC). Provides extensive examples throughout the book to complement the theory presented. Accompanied by a supporting website featuring new material and solutions. More and more students are realizing that they need to learn Bayesian statistics to meet their academic and professional goals. This book is best suited for use as a main text in courses on Bayesian statistics for third and fourth year undergraduates and postgraduate students.

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Kerrie Mengersen L. Case Studies in Bayesian Statistical Modelling and Analysis


Provides an accessible foundation to Bayesian analysis using real world models This book aims to present an introduction to Bayesian modelling and computation, by considering real case studies drawn from diverse fields spanning ecology, health, genetics and finance. Each chapter comprises a description of the problem, the corresponding model, the computational method, results and inferences as well as the issues that arise in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: Illustrates how to do Bayesian analysis in a clear and concise manner using real-world problems. Each chapter focuses on a real-world problem and describes the way in which the problem may be analysed using Bayesian methods. Features approaches that can be used in a wide area of application, such as, health, the environment, genetics, information science, medicine, biology, industry and remote sensing. Case Studies in Bayesian Statistical Modelling and Analysis is aimed at statisticians, researchers and practitioners who have some expertise in statistical modelling and analysis, and some understanding of the basics of Bayesian statistics, but little experience in its application. Graduate students of statistics and biostatistics will also find this book beneficial.

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James Candy V. Bayesian Signal Processing. Classical, Modern, and Particle Filtering Methods


Presents the Bayesian approach to statistical signal processing for a variety of useful model sets This book aims to give readers a unified Bayesian treatment starting from the basics (Baye’s rule) to the more advanced (Monte Carlo sampling), evolving to the next-generation model-based techniques (sequential Monte Carlo sampling). This next edition incorporates a new chapter on “Sequential Bayesian Detection,” a new section on “Ensemble Kalman Filters” as well as an expansion of Case Studies that detail Bayesian solutions for a variety of applications. These studies illustrate Bayesian approaches to real-world problems incorporating detailed particle filter designs, adaptive particle filters and sequential Bayesian detectors. In addition to these major developments a variety of sections are expanded to “fill-in-the gaps” of the first edition. Here metrics for particle filter (PF) designs with emphasis on classical “sanity testing” lead to ensemble techniques as a basic requirement for performance analysis. The expansion of information theory metrics and their application to PF designs is fully developed and applied. These expansions of the book have been updated to provide a more cohesive discussion of Bayesian processing with examples and applications enabling the comprehension of alternative approaches to solving estimation/detection problems. The second edition of Bayesian Signal Processing features: “Classical” Kalman filtering for linear, linearized, and nonlinear systems; “modern” unscented and ensemble Kalman filters: and the “next-generation” Bayesian particle filters Sequential Bayesian detection techniques incorporating model-based schemes for a variety of real-world problems Practical Bayesian processor designs including comprehensive methods of performance analysis ranging from simple sanity testing and ensemble techniques to sophisticated information metrics New case studies on adaptive particle filtering and sequential Bayesian detection are covered detailing more Bayesian approaches to applied problem solving MATLAB® notes at the end of each chapter help readers solve complex problems using readily available software commands and point out other software packages available Problem sets included to test readers’ knowledge and help them put their new skills into practice Bayesian Signal Processing, Second Edition is written for all students, scientists, and engineers who investigate and apply signal processing to their everyday problems.

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Noble Wilford John Bayesian Networks. An Introduction


Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include: An introduction to Dirichlet Distribution, Exponential Families and their applications. A detailed description of learning algorithms and Conditional Gaussian Distributions using Junction Tree methods. A discussion of Pearl's intervention calculus, with an introduction to the notion of see and do conditioning. All concepts are clearly defined and illustrated with examples and exercises. Solutions are provided online. This book will prove a valuable resource for postgraduate students of statistics, computer engineering, mathematics, data mining, artificial intelligence, and biology. Researchers and users of comparable modelling or statistical techniques such as neural networks will also find this book of interest.

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Svein Nyberg Olav The Bayesian Way: Introductory Statistics for Economists and Engineers


A comprehensive resource that offers an introduction to statistics with a Bayesian angle, for students of professional disciplines like engineering and economics The Bayesian Way offers a basic introduction to statistics that emphasizes the Bayesian approach and is designed for use by those studying professional disciplines like engineering and economics. In addition to the Bayesian approach, the author includes the most common techniques of the frequentist approach. Throughout the text, the author covers statistics from a basic to a professional working level along with a practical understanding of the matter at hand. Filled with helpful illustrations, this comprehensive text explores a wide range of topics, starting with descriptive statistics, set theory, and combinatorics. The text then goes on to review fundamental probability theory and Bayes' theorem. The first part ends in an exposition of stochastic variables, exploring discrete, continuous and mixed probability distributions. In the second part, the book looks at statistical inference. Primarily Bayesian, but with the main frequentist techniques included, it covers conjugate priors through the powerful yet simple method of hyperparameters. It then goes on to topics in hypothesis testing (including utility functions), point and interval estimates (including frequentist confidence intervals), and linear regression. This book: Explains basic statistics concepts in accessible terms and uses an abundance of illustrations to enhance visual understanding Has guides for how to calculate the different probability distributions, functions , and statistical properties, on platforms like popular pocket calculators and Mathematica / Wolfram Alpha Includes example-proofs that enable the reader to follow the reasoning Contains assignments at different levels of difficulty from simply filling out the correct formula to the complex multi-step text assignments Offers information on continuous, discrete and mixed probability distributions, hypothesis testing, credible and confidence intervals, and linear regression Written for undergraduate and graduate students of subjects where Bayesian statistics are applied, including engineering, economics, and related fields, The Bayesian Way: With Applications in Engineering and Economics offers a clear understanding of Bayesian statistics that have real-world applications.

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Alexander Kniazev - Wikipedia

Alexandre Alexandrovitch Kniazev (Russian: Александр Александрович Князев) (born 26 April 1961 in Moscow) is a Russian cellist and organist.He was named best musician of the year in Russia in 1999. Kniazev studied music at Moscow Conservatory.. He entered the cello class of Alexander Fedorchenko and in the organ class of G. Kozlova.

Alexander Kniazev, cellist and organist

Alexander Kniazev, cellist and organist Kniazev.homestead.com has been built and maintained by volunteers. The webmaster is grateful to the individuals and organizations who have contributed content and labour to this non-profit site. Images and literary works on this site remain the property of their owners.

Alexander Kniazev, cellist and organist

Alexander Kniazev, cellist and organist Alexander Kniazev was born in Moscow in 1961. He began his cello studies at the age of six with Alexander Fedorchenko and graduated from the Moscow Conservatory in 1986. He then went on to study with the renowned organist Galina Kozlova and graduated from Nizhny-Novgorod Conservatory as an organist in 1991.

Alexander Kniazev | George Enescu Festival

Alexander Kniazev is the worthy successor of Mstislav Rostropovitch and one of Russia’s leading contemporary cellists. Born in 1961 in Moscow, Alexander Kniazev made his debut in 1978 in Russia, England, France, Germany, Italy, Spain, Belgium, Austria, USA, Japan, Korea, South America and South Africa.

Alexander Kniazev – alle CDs – jpc.de

Konstantin Lifschitz (Klavier), Marc Bouchkov (Violine), Ekaterina Astashova (Violine), Andrei Usov (Viola), Alexander Kniazev (Cello) umgehend lieferbar, Bestand beim Lieferanten vorhanden EUR 15,99** CD EUR 14,99* Artikel merken In den Warenkorb Artikel ist im Warenkorb Sergej Rachmaninoff (1873-1943) Symphonien, Klavierkonzerte, Orchesterwerke, Klavierwerke. Nikolai Lugansky, Alexander ...

Alexander Kniazev - Music on Google Play

Alexandre Alexandrovitch Kniazev is a Russian cellist and organist. He was named best musician of the year in Russia in 1999. Kniazev studied music at Moscow Conservatory. He entered the cello class of Alexander Fedorchenko and in the organ class of G. Kozlova. After a solid musical formation, he won first prizes in cello at the Vilnius competition, at that of G. Cassado, the International ...

Alexander Kniazev - Symphoniker Hamburg

Martha Argerich, Thomas Hampson, Alexander Kniazev, Lilya Zilberstein, Geza Hosszu-Legocky, Pablo Barragán, Alexandre Debrus, Mauricio Vallina, Mischa Maisky. So, 28.06.2020 19:00 Uhr. Details. Musik zum Lesen: Sym, Wir geben das völlig neuartige, überregionale Magazin »Sym,« heraus. Der Education-Blog Philine und Johanna mit mehr Infos aus unserem Education-Bereich. Kontakt. Symphoniker ...

Alexander Kniazev - Topic - YouTube

Alexander Kniazev, Constantin Orbelian & Moscow Chamber Orchestra. 21:12 Tchaikovsky : Variations on a Rococo Theme Op.33 3:31 12 Songs Op.60 : XI Exploit View full playlist (13 videos) ...

‎Tchaikovsky : Rococo Variations, Andante Cantabile by ...

Alexander Kniazev, Constantine Orbelian & Moscow Chamber Orchestra Classical · 2005 Preview SONG TIME Tchaikovsky : Variations on a Rococo Theme for 'cello and orchestra op. 33 1976 ...

Tchaikovsky : Rococo Variations, Andante Cantabile ...

Listen to Tchaikovsky : Rococo Variations, Andante Cantabile, Romances on Spotify. Pyotr Ilyich Tchaikovsky · Album · 2005 · 13 songs.

Top Tracks - Alexander Kniazev - YouTube

Top Tracks - Alexander Kniazev Alexander Kniazev - Topic; 153 videos; No views; Updated today; Play all Share. Loading... Save. Sign in to YouTube. Sign in. Berceuse, Op. 20 by Plamena Mangova ...

Alexander Kniazev | Discography | Discogs

Explore releases from Alexander Kniazev at Discogs. Shop for Vinyl, CDs and more from Alexander Kniazev at the Discogs Marketplace.

Alexander Kniazev bei Amazon Music

Im Alexander Kniazev-Shop bei Amazon.de finden Sie alles von Alexander Kniazev (CDs, MP3, Vinyl, etc.) sowie weitere Produkte von und mit Alexander Kniazev (DVDs, Bücher usw.). Entdecken Sie die Biografie und die Diskografie, und reden Sie mit bei den Kundendiskussionen über Alexander Kniazev

Mozart: Cello Sonatas - Alexander Kniazev, Edouard ...

Find album reviews, stream songs, credits and award information for Mozart: Cello Sonatas - Alexander Kniazev, Edouard Oganessian on AllMusic - 2005 - Customarily, the booklet notes for recordings…

Alexander Kniazev - Listen on Deezer | Music Streaming

Alexander Kniazev - Listen to Alexander Kniazev on Deezer. With music streaming on Deezer you can discover more than 56 million tracks, create your own playlists, and share your favourite tracks with your friends.

Astăzi, pe scenele Festivalului George Enescu: Alexander ...

Discografia lui Alexander Kniazev include înregistrări cu lucrări de Bach, Mozart, Brahms, Rahmaninov, Șostakovici, Chopin, Franck, Ysaÿe, o antologie cu lucrări pentru violoncel de Reger, Concertul pentru violoncel, al lui Dvořák, Variațiunile lui Ceaikovski și piesele lui Bloch. Albumele lui au fost primite elogios de critică (Echo Klassik din Germania, Diapason din Franța) și ...

Alexander Kniazev, cello | musicassoluta - musicassoluta ...

Alexander Kniazev also performed as a trio with Boris Berezovsky and Dmitri Makhtin on the prestigious scenes of the Concertgebouw (Amsterdam), at Brussels Palace of Fine Arts, at London Wigmore Hall, at Salzburg Festival, and will soon perform at the Lincoln Center of New York. He played in many prestigious hall like Musikverein of Vienna (with Vladimir Fedoseyev), La Salle Pleyel of Paris ...

Tchaikovsky: Rococo Variations; Nocturne; Andante ...

Find album reviews, stream songs, credits and award information for Tchaikovsky: Rococo Variations; Nocturne; Andante Cantabile; Romances - Alexander Kniazev, Constantine Orbelian, Moscow Chamber Orchestra on AllMusic - 2005

Alexander Kniazev – alle CDs online kaufen

Nikolai Lugansky, Alexander Kniazev, Sheila Armstrong, Robert Tear, John Shirley-Quirk, City of Birmingham Symphony Orchestra, London Symphony Orchestra, Sakari Oramo, Andre Previn Artikel am Lager 8 CDs EUR 21,99* Artikel merken In den Warenkorb Artikel ist im Warenkorb Vakhtang Kakhidze (geb. 1959) Christmas Trilogy für Knaben- und Männerchor & Orchester ...

Bach, JS : Cello Suites Nos 1 - 6 von Alexander Kniazev ...

Alexander Kniazev se fiche apparemment des polémiques sur le style, sur les partis pris interprétatifs, car il propose une conception complètement atypique de ces chefs-d'œuvre de Bach, et se permet des libertés tout bonnement inouïes à ce jour, prêtant ainsi le flanc aux éloges comme à l'indignation...

Alexander Kniazev - Auf Deezer anhören | Musik-Streaming

Alexander Kniazev - Höre Alexander Kniazev auf Deezer. Mit dem Musikstreaming von Deezer kannst du mehr als 56 Millionen Songs entdecken, Tausende Hörbücher, Hörspiele und Podcasts hören, deine eigenen Playlists erstellen und Lieblingssongs mit deinen Freund*innen teilen.

Alexander Knyazev – alle CDs – jpc.de

Alexander Kniazev, Mdzlevari Boys' Choir, Rustavi Choir, Tbilisi Symphony Orchestra, Vakhtang Kakhidze innerhalb von 1-3 Tagen CD EUR 16,99* Artikel merken In den Warenkorb Artikel ist im Warenkorb Verbier Festival - 25 Years of Excellence. Martha Argerich, Daniil Trifonov, Malena Ernman, Yuja Wang, Mikhail Pletnev, Alexander Kniazev, Vadim Repin, Evgeny Kissin, Ilya Gringolts, Truls Mörk ...

Alexander Kniazev – alle CDs online kaufen

Nikolai Lugansky, Alexander Kniazev, Sheila Armstrong, Robert Tear, John Shirley-Quirk, City of Birmingham Symphony Orchestra, London Symphony Orchestra, Sakari Oramo, Andre Previn Artikel am Lager 8 CDs EUR 21,99* Artikel merken In den Warenkorb Artikel ist im Warenkorb Vakhtang Kakhidze (geb. 1959) ...

8. Symphoniekonzert, Congress Innsbruck

Schostakowitsch arbeitete die furchtbare Stalin-Ära in seiner Musik auf, wie im ersten Cellokonzert. Die klingende Autobiographie wird von dem russischen Cellisten Alexander Kniazev offengelegt, der noch mit Mstislav Rostropowitsch musizierte und als dessen legitimer Nachfolger gilt.

Alexander Kniazev - Mariinsky Theatre

Alexander Kniazev was born in 1961 in Moscow. He graduated from the Moscow State Conservatoire in cello (class of Alexander Fyodorchenko) and the Nizhny-Novgorod State Conservatoire in organ (class of Galina Kozlova).

Alexander Kniazev - Bach: Cello Suites 0825646129423 ...

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Recitalul violoncelistului Alexander Kniazev şi al ...

Alexander Kniazev a lucrat cu unele dintre cele mai mari orchestre, printre care Royal Philharmonic Orchestra şi BBC Symphony Orchestra, ambele din Londra, Orchestra Simfonică a Radiodifuziunii Bavareze şi Orchestra Radio din România, dar şi cu ansambluri din Paris, Tokyo, Viena, Luxemburg, Haga, Milano, multe colaborări fiind cu artişti din Rusia.

Chopin* / Rachmaninov*, Alexander Kniazev, Nikolai ...

Chopin* / Rachmaninov*, Alexander Kniazev, Nikolai Lugansky ‎– Cello Sonatas Label: Warner Classics ‎– 2564 63946-2 Format: CD, Album Country: UK & Europe Released: Feb 2007 Genre: Classical . Style: Romantic. Tracklist Hide ...

Tchaikovsky : Rococo Variations, Andante Cantabile ...

Alexander Kniazev is a Russian cellist, born in 1961, with a deep, and really rather relaxed, tone. This decidedly Romantic sound is well suited to this disc of Tchaikovsky cello pieces. Apart from the obvious inclusion of the Variations on a Rococo Theme, Op.33, the Nocturne in D minor, Op.19/4, and the not so uncommonly recorded arrangement (by the composer) of the Andante Cantabile in D ...

Alexander Kniazev - WikiMili, The Best Wikipedia Reader

Alexandre Kniazev during la Folle Journée, 2009.. Alexandre Alexandrovitch Kniazev (Russian: Александр Александрович Князев) (born 26 April 1961 in Moscow) is a Russian cellist and organist.He was named best musician of the year in Russia in 1999. Kniazev studied music at Moscow Conservatory.. He entered the cello class of Alexander Fedorchenko and in the organ ...

ABGESAGT *** Zigeunertrio und Frühlingsopfer - Symphoniker ...

Alexander Kniazev Violoncello Theodosia Ntokou Klavier. Strawinsky »Le sacre du printemps« für zwei Klaviere Martha Argerich und Akane Sakai Klavier. Sie erhalten für das Martha Argerich Festival 2020 Paket-Rabatte: 15 % bei 3 oder 4 Konzerten und 25 % bei 5 oder mehr Konzerten! Der Rabatt wird im Buchungsprozess automatisch angeboten. Sollte dies bei Ihrer Buchung nicht der Fall sein ...

Alexander Kniazev (Cello, Organ) - Short Biography

Alexander Kniazev (Cello, Organ) Born: April 26, 1961 - Moscow, Russia: The Russian cellist and organist, Alexander Kniazev, began his cello studies at the age of 6 with Alexander Fedorchenko and graduated from the Moscow Conservatory in 1986. He then went on to study with the renowned organist Galina Kozlova and graduated from Nizhny-Novgorod Conservatory as an organist in 1991. He received ...

Die Kunst der Kommunikation – Kniazev-Trio

Kniazev-Trio Boris Berezovsky, Dimitri Makhtin und Alexander Kniazev diskutieren, ertasten, verhandeln Rachmaninow und Schostakowitsch. Versuchen eine Annäherung. Erklären Liebe. Sprechen Geheimsprache. Wortlos. Nur mit Klavier, Violine und Cello. Wie eine Gruppe von Verschwörern wirken die Jungs. Einander vertraut, verschwiegen, mit sehr ernstem Blick und ganz klaren Bewegungen. Keine ...

Brahms: Cello sonatas | HIGHRESAUDIO

Alexander Kniazev was born in Moscow in 1961. He began his cello studies at the age of six with Alexander Fedorchenko and graduated from the Moscow Conservatory in 1986. He then went on to study with the renowned organist Galina Kozlova and graduated from Nizhny-Novgorod Conservatory as an organist in 1991. Alexander Kniazev is a laureate of the National Cello Competition in Vilnius (1977 ...

Frederic Chopin, Sergey Rachmaninov, Nikolai Lugansky ...

Chopin's and Rachmaninov's cello sonatas performed by accomplished cellists, Alexander Kniazev and Nikolai Lugansky. Product details. Performer: Nikolai Lugansky, Alexander Kniazev; Composer: Frederic Chopin, Sergey Rachmaninov; Audio CD (February 27, 2007) SPARS Code: DDD; Number of Discs: 1; Label: Warner Classics; ASIN: B000KGGLH0; Customer Reviews: 4.6 out of 5 stars 4 customer ratings ...

Violocelistul Alexander Kniazev şi pianista Plamena ...

ALEXANDER KNIAZEV violoncel. PLAMENA MANGOVA pian. Program: Enescu – Sonata I în fa minor pentru pian şi violoncel, op. 26 nr.1 . Brahms – Sonata nr. 2 în Fa major pentru violoncel şi pian, op. 99. Franck – Sonata în La major pentru vioară şi pian, în versiune pentru violoncel . Dacă apreciezi acest articol, te așteptăm să intri în comunitatea de cititori de pe pagina ...

klassik.com : Alexander Kniazev engagieren / buchen ...

Alexander Kniazev Alexander Kniazev für Konzert engagieren - Ihr Kontakt zum Konzert-Management oder zur Konzertagentur Um Alexander Kniazev für ein Konzert oder eine Veranstaltung zu buchen, können Sie mit den nachfolgend aufgelisteten Agenturen Kontakt aufnehmen. Die Kontaktmöglichkeit können Sie ebenfalls nutzen, wenn Sie auf der Suche nach einem Autogramm oder einer Liste der ...

Alexander Kniazev, Edouard Oganessian - Mozart: Cello ...

Alexander Kniazev - cello Edouard Oganessian – piano. Customarily, the booklet notes for recordings containing music transcribed for instruments other than those for which it was written make the argument that such transcriptions were normal, accepted, and so on, in the years when the music was written. The ones for this disc make the same argument, but it's not so relevant in this case ...

Plamena Mangova - Solo Musica

Auf ihrer neuesten CD, ebenfalls hochgelobt, hat sie mit dem Cellisten Alexander Kniazev Werke von Franck und Ysaye eingespielt. Diskografie. Diese Website verwendet Cookies. Mit der weiteren Nutzung stimmen Sie ihrer Verwendung zu. This website uses cookies. By continuing to use it, you agree to their use. Informationen zu Datenschutz und Cookies SOLO MUSICA GMBH. Agnes-Bernauer-Str. 181 ...

Alexander Kniazev - MusicBrainz

cellist, Type: Person, Gender: Male, Born: 1961-04-26 in Moskva, Area: Russia

Boris Wadimowitsch Beresowski – Wikipedia

Boris Berezovsky / Dmitri Makhtin / Alexander Kniazev — «Les Pianos De La Nuit». Tschaikowsky: «Jahreszeiten» (Nr. 6: Barcarolle – Juni); Nocturne D-Moll nach Klavierstück, Op. 19 Nr. 4; Trio für Klavier, Geige und Cello, Op. 50; Melancholische Serenade B-Moll, Op. 26. Regie: Andy Sommer. Aufnahme 10. August 2004 (Naïve 2006)

Organ Riga Dome Cathedral Alexander Kniazev auf CD online ...

Jetzt Alexander Kniazev - Organ Riga Dome Cathedral - (CD) im SATURN Onlineshop kaufen Günstiger Versand & Kostenlose Marktabholung Bester Service direkt im Markt

Alexander Kniazev - Bach, JS : Cello Suites Nos 1 - 6 ...

Bach, JS : Cello Suites Nos 1 - 6 - Alexander Kniazev. Klicke einfach auf einen der folgenden Titel, um dir dir den entsprechenden Songtext anzeigen zu lassen oder drücke den Play Button, um dir einen Ausschnitt des jeweiligen Songs anzuhören: # Titel Anhören; 1: Alexander Kniazev - Bach, JS : Cello Suite No.1 in G major BWV1007 : I Prelude [Songtext anzeigen] 2: Alexander Kniazev - Bach ...

Un recital cameral de înaltă ținută al artiștilor ...

Concertele lui Alexander Kniazev au fost recompensate cu ovații în întreaga lume, în săli prestigioase cum ar fi Concertgebouw din Amsterdam, Salle Pleyel și Théâtre des Champs Élysées din Paris, Palais des Beaux Arts din Bruxelles, Wigmore Hall și Royal Festival Hall din Londra, Mozarteum din Salzburg, Musikverein și Konzerthaus din Viena.

Alexander Kniazev Songtexte, Lyrics & Übersetzungen

Alexander Kniazev Diskografie. Klicke einfach auf eines der folgenden Alben, um dir die Songtexte anzeigen zu lassen: Alexander Kniazev - J.S.Bach: Six Suites for Violoncello solo - Chaconne Alexander Kniazev - Rachmaninov & Chopin : Cello Sonatas Alexander Kniazev - Bach, JS : Cello Suite No.1 Alexander Kniazev - Bach, JS : Cello Suite No.2 Alexander Kniazev - Bach, JS : Cello Suite No.3 ...

Liste der Echo-Klassik-Preisträger – Wikipedia

Alexander Kniazev, Constantine Orbelian, Moscow Chamber Orchestra (P. Tschaikowsky: Rococo Variations – Nocturne – Andante cantabile – Romances) (Musik des 19. Jahrhunderts) Baiba Skride (D. Schostakowitsch, L. Jancek: Violin Konzerte) (Musik des 20./21. Jahrhunderts)

Cellosonaten Alexander Kniazev, Andrei Korobeinikov auf CD ...

Jetzt Alexander Kniazev, Andrei Korobeinikov - Cellosonaten - (CD) im SATURN Onlineshop kaufen Günstiger Versand & Kostenlose Marktabholung Bester Service direkt im Markt

4. Abo-Konzert / Arp Museum Rolandseck

Alexander Kniazev, Plamena Mangova. Richard Strauss: Klavierquartett c-Moll op. 13 Enrico Pace, Isabelle van Keulen, Razvan Popovici, Alexander Kniazev. Das gesamte Programm finden Sie hier. Karten und Preise: Abonnement für fünf Konzerte: 135,- Euro – die Karten sind übertragbar. Einzeltickets: 35,- Euro, erm. 20,- Euro

Brani Vidakovic Engineering Biostatistics. An Introduction using MATLAB and WinBUGS


Provides a one-stop resource for engineers learning biostatistics using MATLAB® and WinBUGS Through its scope and depth of coverage, this book addresses the needs of the vibrant and rapidly growing bio-oriented engineering fields while implementing software packages that are familiar to engineers. The book is heavily oriented to computation and hands-on approaches so readers understand each step of the programming. Another dimension of this book is in parallel coverage of both Bayesian and frequentist approaches to statistical inference. It avoids taking sides on the classical vs. Bayesian paradigms, and many examples in this book are solved using both methods. The results are then compared and commented upon. Readers have the choice of MATLAB® for classical data analysis and WinBUGS/OpenBUGS for Bayesian data analysis. Every chapter starts with a box highlighting what is covered in that chapter and ends with exercises, a list of software scripts, datasets, and references. Engineering Biostatistics: An Introduction using MATLAB® and WinBUGS also includes: parallel coverage of classical and Bayesian approaches, where appropriate substantial coverage of Bayesian approaches to statistical inference material that has been classroom-tested in an introductory statistics course in bioengineering over several years exercises at the end of each chapter and an accompanying website with full solutions and hints to some exercises, as well as additional materials and examples Engineering Biostatistics: An Introduction using MATLAB® and WinBUGS can serve as a textbook for introductory-to-intermediate applied statistics courses, as well as a useful reference for engineers interested in biostatistical approaches.

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Eugene Hahn D. Bayesian Methods for Management and Business. Pragmatic Solutions for Real Problems


HIGHLIGHTS THE USE OF BAYESIAN STATISTICS TO GAIN INSIGHTS FROM EMPIRICAL DATA Featuring an accessible approach, Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems demonstrates how Bayesian statistics can help to provide insights into important issues facing business and management. The book draws on multidisciplinary applications and examples and utilizes the freely available software WinBUGS and R to illustrate the integration of Bayesian statistics within data-rich environments. Computational issues are discussed and integrated with coverage of linear models, sensitivity analysis, Markov Chain Monte Carlo (MCMC), and model comparison. In addition, more advanced models including hierarchal models, generalized linear models, and latent variable models are presented to further bridge the theory and application in real-world usage. Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems also features: Numerous real-world examples drawn from multiple management disciplines such as strategy, international business, accounting, and information systems An incremental skill-building presentation based on analyzing data sets with widely applicable models of increasing complexity An accessible treatment of Bayesian statistics that is integrated with a broad range of business and management issues and problems A practical problem-solving approach to illustrate how Bayesian statistics can help to provide insight into important issues facing business and management Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems is an important textbook for Bayesian statistics courses at the advanced MBA-level and also for business and management PhD candidates as a first course in methodology. In addition, the book is a useful resource for management scholars and practitioners as well as business academics and practitioners who seek to broaden their methodological skill sets.

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Sondipon Adhikari Probabilistic Finite Element Model Updating Using Bayesian Statistics. Applications to Aeronautical and Mechanical Engineering


Probabilistic Finite Element Model Updating Using Bayesian Statistics: Applications to Aeronautical and Mechanical Engineering Tshilidzi Marwala and Ilyes Boulkaibet, University of Johannesburg, South Africa Sondipon Adhikari, Swansea University, UK Covers the probabilistic finite element model based on Bayesian statistics with applications to aeronautical and mechanical engineering Finite element models are used widely to model the dynamic behaviour of many systems including in electrical, aerospace and mechanical engineering. The book covers probabilistic finite element model updating, achieved using Bayesian statistics. The Bayesian framework is employed to estimate the probabilistic finite element models which take into account of the uncertainties in the measurements and the modelling procedure. The Bayesian formulation achieves this by formulating the finite element model as the posterior distribution of the model given the measured data within the context of computational statistics and applies these in aeronautical and mechanical engineering. Probabilistic Finite Element Model Updating Using Bayesian Statistics contains simple explanations of computational statistical techniques such as Metropolis-Hastings Algorithm, Slice sampling, Markov Chain Monte Carlo method, hybrid Monte Carlo as well as Shadow Hybrid Monte Carlo and their relevance in engineering. Key features: Contains several contributions in the area of model updating using Bayesian techniques which are useful for graduate students. Explains in detail the use of Bayesian techniques to quantify uncertainties in mechanical structures as well as the use of Markov Chain Monte Carlo techniques to evaluate the Bayesian formulations. The book is essential reading for researchers, practitioners and students in mechanical and aerospace engineering.

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Jochen Voss An Introduction to Statistical Computing. A Simulation-based Approach


A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods. An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced methods such as the reversible jump Markov chain Monte Carlo algorithm and modern methods such as approximate Bayesian computation and multilevel Monte Carlo techniques An Introduction to Statistical Computing: Fully covers the traditional topics of statistical computing. Discusses both practical aspects and the theoretical background. Includes a chapter about continuous-time models. Illustrates all methods using examples and exercises. Provides answers to the exercises (using the statistical computing environment R); the corresponding source code is available online. Includes an introduction to programming in R. This book is mostly self-contained; the only prerequisites are basic knowledge of probability up to the law of large numbers. Careful presentation and examples make this book accessible to a wide range of students and suitable for self-study or as the basis of a taught course

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Lawson Andrew B. Bayesian Biostatistics


The growth of biostatistics has been phenomenal in recent years and has been marked by considerable technical innovation in both methodology and computational practicality. One area that has experienced significant growth is Bayesian methods. The growing use of Bayesian methodology has taken place partly due to an increasing number of practitioners valuing the Bayesian paradigm as matching that of scientific discovery. In addition, computational advances have allowed for more complex models to be fitted routinely to realistic data sets. Through examples, exercises and a combination of introductory and more advanced chapters, this book provides an invaluable understanding of the complex world of biomedical statistics illustrated via a diverse range of applications taken from epidemiology, exploratory clinical studies, health promotion studies, image analysis and clinical trials. Key Features: Provides an authoritative account of Bayesian methodology, from its most basic elements to its practical implementation, with an emphasis on healthcare techniques. Contains introductory explanations of Bayesian principles common to all areas of application. Presents clear and concise examples in biostatistics applications such as clinical trials, longitudinal studies, bioassay, survival, image analysis and bioinformatics. Illustrated throughout with examples using software including WinBUGS, OpenBUGS, SAS and various dedicated R programs. Highlights the differences between the Bayesian and classical approaches. Supported by an accompanying website hosting free software and case study guides. Bayesian Biostatistics introduces the reader smoothly into the Bayesian statistical methods with chapters that gradually increase in level of complexity. Master students in biostatistics, applied statisticians and all researchers with a good background in classical statistics who have interest in Bayesian methods will find this book useful.

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A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistical models, including the multiple linear regression model, the hierarchical mean model, the logistic regression model, and the proportional hazards model. The book begins with an outline of the similarities and differences between Bayesian and the likelihood approaches to statistics. Subsequent chapters present key techniques for using computer software to draw Monte Carlo samples from the incompletely known posterior distribution and performing the Bayesian inference calculated from these samples. Topics of coverage include: Direct ways to draw a random sample from the posterior by reshaping a random sample drawn from an easily sampled starting distribution The distributions from the one-dimensional exponential family Markov chains and their long-run behavior The Metropolis-Hastings algorithm Gibbs sampling algorithm and methods for speeding up convergence Markov chain Monte Carlo sampling Using numerous graphs and diagrams, the author emphasizes a step-by-step approach to computational Bayesian statistics. At each step, important aspects of application are detailed, such as how to choose a prior for logistic regression model, the Poisson regression model, and the proportional hazards model. A related Web site houses R functions and Minitab macros for Bayesian analysis and Monte Carlo simulations, and detailed appendices in the book guide readers through the use of these software packages. Understanding Computational Bayesian Statistics is an excellent book for courses on computational statistics at the upper-level undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners who use computer programs to conduct statistical analyses of data and solve problems in their everyday work.

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Biao Huang Process Control System Fault Diagnosis. A Bayesian Approach


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An introduction to Crystallography


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Workbook to accompany Introduction to Biostatistical Applications in Health Research with Microsoft Office Excel—practical and methodological approach to the statistical logic of biostatistics in the field of health research.

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