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1. |
Record Nr. |
UNISA996387441503316 |
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Autore |
Collier Thomas |
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Titolo |
An answer to an epistle, written by Thomas Salthouse, to the churches of the Anabaptists, so called [[electronic resource] ] : wherein his epistle being weighed in the ballance, is found too light : with a word to the churches and another to the people called Quakers : to the law and to the testimony, if any speak not according to this rule, it is because there is no light in them |
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Pubbl/distr/stampa |
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Descrizione fisica |
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Soggetti |
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Society of Friends - England |
Quakers - England |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Caption title. |
Signed at end: Thomas Collier. |
Imprint suggested by Wing (2nd ed.). |
Imperfect: stained and torn with some loss of text. |
Reproduction of original in: Library of Congress. |
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Sommario/riassunto |
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2. |
Record Nr. |
UNINA9910863136103321 |
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Autore |
Golyandina Nina |
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Titolo |
Singular Spectrum Analysis for Time Series / / by Nina Golyandina, Anatoly Zhigljavsky |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[2nd ed. 2020.] |
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Descrizione fisica |
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1 online resource (IX, 146 p. 44 illus., 38 illus. in color.) |
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Collana |
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SpringerBriefs in Statistics, , 2191-5458 |
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Disciplina |
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Soggetti |
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Statistics |
Signal processing |
Biometry |
Statistical Theory and Methods |
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences |
Signal, Speech and Image Processing |
Statistics in Business, Management, Economics, Finance, Insurance |
Biostatistics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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1 Introduction -- 1.1 Overview of SSA methodology and the structure of the book -- 1.2 SSA and other techniques -- 1.3 Computer implementation of SSA -- 1.4 Historical and bibliographical remarks -- 1.5 Common symbols and acronyms -- 2 Basic SSA - 2.1 The main algorithm -- 2.2 Potential of Basic SSA -- 2.3 Models of time series and SSA objectives -- 2.4 Choice of parameters in Basic SSA -- 2.5 Some variations of Basic SSA -- 2.6 Multidimensional and multivariate extensions of SSA -- 3 SSA for forecasting, interpolation, filtering and estimation -- 3.1 SSA forecasting algorithms -- 3.2 LRR and associated characteristic polynomials -- 3.3 Recurrent forecasting as approximate continuation -- 3.4 Confidence bounds for the forecasts -- 3.5 Summary and recommendations on forecasting parameters -- 3.6 Case study: ‘Fortified wine’ -- 3.7 Imputation of missing values -- 3.8 Subspace-based methods and estimation of signal parameters -- 3.9 |
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SSA and filters -- 3.10 Multidimensional/Multivariate SSA. |
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Sommario/riassunto |
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This book gives an overview of singular spectrum analysis (SSA). SSA is a technique of time series analysis and forecasting combining elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. SSA is multi-purpose and naturally combines both model-free and parametric techniques, which makes it a very special and attractive methodology for solving a wide range of problems arising in diverse areas. Rapidly increasing number of novel applications of SSA is a consequence of the new fundamental research on SSA and the recent progress in computing and software engineering which made it possible to use SSA for very complicated tasks that were unthinkable twenty years ago. In this book, the methodology of SSA is concisely but at the same time comprehensively explained by two prominent statisticians with huge experience in SSA. The book offers a valuable resource for a very wide readership, including professional statisticians, specialists in signal and image processing, as well as specialists in numerous applied disciplines interested in using statistical methods for time series analysis, forecasting, signal and image processing. The second edition of the book contains many updates and some new material including a thorough discussion on the place of SSA among other methods and new sections on multivariate and multidimensional extensions of SSA. |
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