| 000 | 03419nam a22004575i 4500 | ||
|---|---|---|---|
| 001 | 978-0-387-28393-7 | ||
| 003 | DE-He213 | ||
| 005 | 20250710083941.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 100301s2005 xxu| s |||| 0|eng d | ||
| 020 |
_a9780387283937 _a99780387283937 |
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| 024 | 7 |
_a10.1007/0-387-28393-5 _2doi |
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| 082 | 0 | 4 |
_a519.5 _223 |
| 100 | 1 |
_aClarkson, Douglas B. _eauthor. |
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| 245 | 1 | 0 |
_aS+ Functional Data Analysis _h[recurso electrónico] : _bUser's Manual for Windows® / _cby Douglas B. Clarkson, Chris Fraley, Charles C. Gu, James O. Ramsey. |
| 264 | 1 |
_aNew York, NY : _bSpringer New York, _c2005. |
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| 300 |
_aX, 192 p. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_arecurso en línea _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 505 | 0 | _aBasis Objects and Operations -- Functional Data Objects and Operations -- Linear Differential Operators and Smoothing -- Functional Registration -- Functional Linear Models -- Functional Generalized Linear Models -- Functional Principal Components -- Canonical Correlation -- Functional Cluster Analysis -- Principal Differential Analysis. | |
| 520 | _aS+Functional Data Analysis is the first commercial object oriented package for exploring, modeling, and analyzing functional data. Functional data analysis (FDA) handles longitudinal data and treats each observation as a function of time (or other variable). The functions are related. The goal is to analyze a sample of functions instead of a sample of related points. FDA differs from traditional data analytic techniques in a number of ways. Functions can be evaluated at any point in their domain. Derivatives and integrals, which may provide better information (e.g. graphical) than the original data, are easily computed and used in multivariate and other functional analytic methods. The analyst using S+FDA can handle irregularly spaced data or data with missing values. For large amounts of data, working with a functional representation can save storage. Moreover, S+FDA provides a variety of analytic techniques for functional data including linear models, generalized linear models, principal components, canonical correlation, principal differential analysis, and clustering. This book can be considered a companion to two other highly acclaimed books involving James Ramsay and Bernard Silverman: Functional Data Analysis, Second Edition (2005) and Applied Functional Data Analysis (2002). This user's manual also provides the documentation for the S+FDA library for SPlus. | ||
| 650 | 0 | _aSTATISTICS. | |
| 650 | 0 | _aMATHEMATICAL STATISTICS. | |
| 650 | 1 | 4 | _aSTATISTICS. |
| 650 | 2 | 4 | _aSTATISTICS AND COMPUTING/STATISTICS PROGRAMS. |
| 650 | 2 | 4 | _aSTATISTICAL THEORY AND METHODS. |
| 650 | 2 | 4 | _aSTATISTICS FOR ENGINEERING, PHYSICS, COMPUTER SCIENCE, CHEMISTRY & GEOSCIENCES. |
| 650 | 2 | 4 | _aSTATISTICS FOR LIFE SCIENCES, MEDICINE, HEALTH SCIENCES. |
| 700 | 1 |
_aFraley, Chris. _eauthor. |
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| 700 | 1 |
_aGu, Charles C. _eauthor. |
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| 700 | 1 |
_aRamsey, James O. _eauthor. |
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| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9780387249698 |
| 856 | 4 | 0 |
_uhttp://dx.doi.org/10.1007/0-387-28393-5 _zVer el texto completo en las instalaciones del CICY |
| 912 | _aZDB-2-SMA | ||
| 942 |
_2ddc _cER |
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| 999 |
_c56821 _d56821 |
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