| Judul | Model-Based Recursive Partitioning with Adjustment for Measurement Error / Hanna Birke |
| Pengarang | Birke, Hanna |
| Penerbitan | Abraham-Lincoln-Straße 46 65189, Wiesbaden, Germany : Springer Fachmedien Wiesbaden, 2015 |
| Deskripsi Fisik | 240 :ill |
| ISBN | 978-3-658-08505-6 |
| Subjek | COMPUTATIONAL MATHEMATICS AND NUMERICAL ANALYSIS MATHEMATICAL AND COMPUTATIONAL BIOLOGY CANCER RESEARCH |
| Abstrak | ?Model-based recursive partitioning (MOB) provides a powerful synthesis between machine-learning inspired recursive partitioning methods and regression models. Hanna Birke extends this approach by allowing in addition for measurement error in covariates, as frequently occurring in biometric (or econometric) studies, for instance, when measuring blood pressure or caloric intake per day. After an introduction into the background, the extended methodology is developed in detail for the Cox model and the Weibull model, carefully implemented in R, and investigated in a comprehensive simulation study. |
| Bentuk Karya | Tidak ada kode yang sesuai |
| Target Pembaca | Tidak ada kode yang sesuai |
| Lokasi Akses Online |
http://link.springer.com/openurl?genre=book&isbn=978-3-658-08504-9 |
| No Barcode | No. Panggil | Akses | Lokasi | Ketersediaan |
|---|---|---|---|---|
| 193515292 | 518 Bir m | Baca Online | Perpustakaan Pusat - Online Resources Ebook |
Tersedia |
| Tag | Ind1 | Ind2 | Isi |
| 001 | INLIS000000000159376 | ||
| 005 | 20250318095629 | ||
| 007 | ta | ||
| 008 | 250318################|##########|#|## | ||
| 020 | # | # | $a 978-3-658-08505-6 |
| 035 | # | # | $a 0010-0325000995 |
| 082 | # | # | $a 518 |
| 084 | # | # | $a 518 Bir m |
| 100 | 0 | # | $a Birke, Hanna |
| 245 | 1 | # | $a Model-Based Recursive Partitioning with Adjustment for Measurement Error /$c Hanna Birke |
| 260 | # | # | $a Abraham-Lincoln-Straße 46 65189, Wiesbaden, Germany :$b Springer Fachmedien Wiesbaden,$c 2015 |
| 300 | # | # | $a 240 : $b ill |
| 520 | # | # | $a ?Model-based recursive partitioning (MOB) provides a powerful synthesis between machine-learning inspired recursive partitioning methods and regression models. Hanna Birke extends this approach by allowing in addition for measurement error in covariates, as frequently occurring in biometric (or econometric) studies, for instance, when measuring blood pressure or caloric intake per day. After an introduction into the background, the extended methodology is developed in detail for the Cox model and the Weibull model, carefully implemented in R, and investigated in a comprehensive simulation study. |
| 650 | # | # | $a CANCER RESEARCH |
| 650 | # | # | $a COMPUTATIONAL MATHEMATICS AND NUMERICAL ANALYSIS |
| 650 | # | # | $a MATHEMATICAL AND COMPUTATIONAL BIOLOGY |
| 856 | # | # | $a http://link.springer.com/openurl?genre=book&isbn=978-3-658-08504-9 |
| 990 | # | # | $a 193515292 |
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