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02081cam a2200433Ia 4500 |
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990000609450204151 |
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20241030112643.0 |
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110604s2011 gw a b 001 0 eng d |
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|a 2011930793
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|a 9783642201912
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|a 3642201911
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|z 9783642201929 (e-ISBN)
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|z 364220192X (e-ISBN)
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|a (OCoLC)000060945
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| 035 |
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|a (udesa)000060945USA01
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| 035 |
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|a (OCoLC)729346867
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|a (OCoLC)990000609450204151
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|a BTCTA
|b eng
|c BTCTA
|d YDXCP
|d OHX
|d AZS
|d BWX
|d CDX
|d MUU
|d MEAUC
|d NJT
|d FDA
|d OCLCQ
|d U@S
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| 049 |
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|a U@SA
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| 050 |
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4 |
|a QA276
|b .B84 2011
|
| 100 |
1 |
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|a Bühlmann, Peter.
|
| 245 |
1 |
0 |
|a Statistics for high-dimensional data :
|b methods, theory and applications /
|c Peter Bühlmann, Sara van de Geer.
|
| 260 |
|
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|a Heidelberg ;
|a New York :
|b Springer-Verlag,
|c c2011.
|
| 300 |
|
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|a xvii, 556 p. :
|b ill. (some col.) ;
|c 24 cm.
|
| 490 |
1 |
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|a Springer series in statistics
|
| 504 |
|
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|a Includes bibliographical references (p. 547-556) and indexes.
|
| 505 |
0 |
|
|a Introduction -- Lasso for linear models -- Generalized linear models and the Lasso -- The group Lasso --Additive models and many smooth univariate functions -- Theory for the Lasso -- Variable selection with the Lasso -- Theory for l1/l2-penalty procedures -- Non-convex loss functions and l1-regulation -- Stable solutions -- P-values for linear models and beyond -- Boosting and greedy algorithms -- Graphical modeling -- Probabililty and moment inequalities.
|
| 650 |
|
0 |
|a Mathematical statistics.
|
| 650 |
|
0 |
|a Smoothness of functions.
|
| 650 |
|
0 |
|a Nonconvex programming.
|
| 650 |
|
0 |
|a Least absolute deviations (Statistics)
|
| 650 |
|
0 |
|a Linear models (Statistics)
|
| 650 |
|
7 |
|a Estadística matemática.
|2 UDESA
|
| 650 |
|
7 |
|a Funciones continuamente diferenciables.
|2 UDESA
|
| 650 |
|
7 |
|a Programación no convexa.
|2 UDESA
|
| 650 |
|
7 |
|a Desviaciones mínimas absolutas (Estadística)
|2 UDESA
|
| 650 |
|
7 |
|a Modelos lineales (Estadística)
|2 UDESA
|
| 700 |
1 |
|
|a Geer, S. A. van de
|q (Sara A.)
|
| 830 |
|
0 |
|a Springer series in statistics
|