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Calf roping --- Lasso. --- Trick roping. --- Trick roping --- Social Sciences --- Recreation & Sports --- Roping, Calf --- Rodeos --- Rope spinning --- Roping, Trick --- Spinning, Rope --- Tricks --- Lasso --- Rope --- Bolas --- History. --- History
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After the Mass Ordinary, the Magnificat was the liturgical text most frequently set by Renaissance composers, and Orlando di Lasso's 101 polyphonic settings form the largest and most varied repertory of Magnificats in the history of European music. In the first detailed investigation of this repertory, David Crook focuses on the forty parody or imitation Magnificats, which Lasso based on motets, madrigals, and chansons written by such composers as Josquin and Rore. By examining these Magnificats in their social, historical, and liturgical contexts and in terms of composition theory, Crook opens a new window on the breadth and subtlety of an important composer often harshly judged on his use of preexistent music.Crook places Lasso amidst the Counter-Reformation reforms at the Bavarian court where he composed the Magnificats, and where there emerged a fanatical Marian cult that favored this genre. In a section on compositional procedure, Crook explains that Lasso abandoned the traditional eight psalm-tone melodies in his imitation Magnificats, considers the new ways he found to represent the tones, and describes how Lasso's experimentation reflected the complex relationship between mode and tone in Renaissance theory and practice. Arguing that Lasso's varied uses of preexistent music defy current definitions of parody technique, Crook, in his final chapter, reveals the imitation Magnificats as vastly more imaginative and innovative than previous characterizations suggest.Originally published in 1994.The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
Magnificat (Music) --- Church music --- History and criticism --- History and criticism. --- Lasso, Orlando di, --- -Church music --- Pastoral music (Sacred) --- Religious music --- Sacred vocal music --- Devotional exercises --- Liturgics --- Music --- Music in churches --- Psalmody --- Evening service music --- Religious aspects --- Christianity --- Lasso, Orlando di --- Munich (Germany) --- 16th century --- 526.30 --- Genre- en werkbesprekingen
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Garcilaso de la Vega --- Spaanse poëzie. 16e eeuw. --- Garcilaso de la Vega. --- Poésie espagnole. 16e s. --- Spanish poetry --- Vega, Garcilaso de la, --- De la Vega, Garcilaso, --- Laso de la Vega, --- Lasso de la Vega, --- La Vega, Garcilaso de, --- Garcilaso de la Vega, --- Vega, García Laso de la, --- Suárez de Figueroa, García, --- De Figueroa, García Suárez, --- Figueroa, García Suárez de, --- Garci-Lasso de la Vega, --- Influence.
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"Garcilaso de la Vega and the Material Culture of Renaissance Europe examines the role of cultural objects in the lyric poetry of Garcilaso de la Vega, the premier poet of sixteenth-century Spain. As a pioneer of the 'new poetry' of Renaissance Europe, aligned with the court, empire, and modernity, Garcilaso was fully attuned to the collection and circulation of luxury artefacts and other worldly goods. In his poems, a variety of objects, including tapestries, paintings, statues, urns, mirrors, and relics participate in lyric acts of discovery and self-revelation, reveal memory as contingent and unstable, expose knowledge of the self as deceptive, and show how history intersects with the ideology of empire."--Publisher's web site
Renaissance --- material culture [discipline] --- Vega, de la, Garcilasso --- Authors, Spanish --- Ecrivains espagnols --- Vega, Garcilaso de la, --- Material culture in literature. --- Material culture --- History --- Criticism and interpretation. --- De la Vega, Garcilaso, --- Laso de la Vega, --- Lasso de la Vega, --- La Vega, Garcilaso de, --- Garcilaso de la Vega, --- Vega, García Laso de la, --- Suárez de Figueroa, García, --- De Figueroa, García Suárez, --- Figueroa, García Suárez de, --- Garci-Lasso de la Vega, --- Culture --- Folklore --- Technology --- 1500 - 1599 --- Europe. --- Council of Europe countries --- Eastern Hemisphere --- Eurasia --- cultuurgeschiedenis
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Mahler, Gustav --- Composition (Music) --- Mass (Music) --- Parody in music. --- Composition (Music). --- Mass (Music). --- Parody (Music) --- Musical parodies --- Musical parody --- Musical form --- Humor in music --- Masses --- Composing (Music) --- Music composing --- Music composition --- Musical composition --- Concertante style --- Lasso, Orlando di --- Music --- History and criticism --- Composition --- Church music --- Lord's Supper (Liturgy) --- Catholic Church --- Mahler, Gustav. --- Maler, Gustav, --- Maler, G. --- Mārā, Gusutafu, --- Lassus, Roland de
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Boscán, Juan, --- Vega, Garcilaso de la, --- Petrarca, Francesco, --- Pétrarque --- Petrarch --- Petracco, Francesco --- Petrarca, Francesco (1304-1374) --- De la Vega, Garcilaso, --- Laso de la Vega, --- Lasso de la Vega, --- La Vega, Garcilaso de, --- Garcilaso de la Vega, --- Vega, García Laso de la, --- Suárez de Figueroa, García, --- De Figueroa, García Suárez, --- Figueroa, García Suárez de, --- Garci-Lasso de la Vega, --- Almogaver, Juan Boscán, --- Boscà Almogàver, Joan, --- Boscà, Joan, --- Boscán Almogaver, Juan, --- Criticism and interpretation. --- Influence. --- Petrarca, Franciscus, --- Petrarch, --- Petrarch, Francesco, --- Petrarcha, Franciscus, --- Petrark, --- Petrarka, Franchesko, --- Peṭrarḳa, Frants'esḳo, --- Pétrarque, --- Петрарка, Франческо, --- פטררקא, פרנצ׳סקו --- Boscan, Juan --- Criticism and interpretation --- Vega, Garcilaso de la --- Petrarca, Francesco --- Influence --- Boscan, Juan,
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"This authoritative book draws on the latest research to explore the interplay of high-dimensional statistics with optimization. Through an accessible analysis of fundamental problems of hypothesis testing and signal recovery, Anatoli Juditsky and Arkadi Nemirovski show how convex optimization theory can be used to devise and analyze near-optimal statistical inferences. Statistical Inference via Convex Optimization is an essential resource for optimization specialists who are new to statistics and its applications, and for data scientists who want to improve their optimization methods. Juditsky and Nemirovski provide the first systematic treatment of the statistical techniques that have arisen from advances in the theory of optimization. They focus on four well-known statistical problems-sparse recovery, hypothesis testing, and recovery from indirect observations of both signals and functions of signals-demonstrating how they can be solved more efficiently as convex optimization problems. The emphasis throughout is on achieving the best possible statistical performance. The construction of inference routines and the quantification of their statistical performance are given by efficient computation rather than by analytical derivation typical of more conventional statistical approaches. In addition to being computation-friendly, the methods described in this book enable practitioners to handle numerous situations too difficult for closed analytical form analysis, such as composite hypothesis testing and signal recovery in inverse problems. Statistical Inference via Convex Optimization features exercises with solutions along with extensive appendixes, making it ideal for use as a graduate text"--
Mathematical statistics. --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Statistical methods --- All of Nonparametric Statistics. --- Asymptotic Methods in Statistical Decision Theory. --- Dantzig selector. --- Gaussian observations. --- Has'minskii. --- Hellinger distance. --- Ibragimov. --- Introduction to Nonparametric Estimation. --- Lagrange duality. --- Le Cam. --- N-convex function. --- Statistical Estimation. --- Tsybakov. --- Wasserman. --- bisection algorithm. --- conic programming. --- convex sets. --- duality. --- ell-1-norm minimization. --- estimating functions. --- lasso selector. --- minimization. --- saddle points. --- signal plus noise. --- signal-to-noise. --- unobserved signal. --- variable selection.
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Model selection and forecasting in stress tests can be facilitated using machine learning techniques. These techniques have proved robust in other fields for dealing with the curse of dimensionality, a situation often encountered in applied stress testing. Lasso regressions, in particular, are well suited for building forecasting models when the number of potential covariates is large, and the number of observations is small or roughly equal to the number of covariates. This paper presents a conceptual overview of lasso regressions, explains how they fit in applied stress tests, describes its advantages over other model selection methods, and illustrates their application by constructing forecasting models of sectoral probabilities of default in an advanced emerging market economy.
Recessions. --- Lasso. --- Rope --- Bolas --- Trick roping --- Business cycles --- Depressions --- Banks and Banking --- Foreign Exchange --- Investments: General --- Macroeconomics --- Forecasting and Other Model Applications --- Banks --- Depository Institutions --- Micro Finance Institutions --- Mortgages --- Price Level --- Inflation --- Deflation --- Interest Rates: Determination, Term Structure, and Effects --- General Financial Markets: General (includes Measurement and Data) --- Currency --- Foreign exchange --- Banking --- Investment & securities --- Consumer price indexes --- Central bank policy rate --- Nominal effective exchange rate --- Treasury bills and bonds --- Real effective exchange rates --- Prices --- Financial services --- Financial institutions --- Price indexes --- Interest rates --- Government securities --- United States
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